W. E. B. Du BoisThe Souls of Black Folk(1903) Essays - Free Essays

W. E. B. Du Bois'The Souls of Black Folk(1903) Essays - Free Essays W. E. B. Du Bois'The Souls of Black Folk(1903) is an original work in African American writing and an American exemplary. In this work Du Bois recommends that the issue of the Twentieth Century is the issue of the shading line. His ideas of life behind the cloak of race and the subsequent twofold cognizance, this feeling of continually taking a gander at one's self through the eyes of others, have become touchstones for considering race in America. Notwithstanding these suffering concepts,Soulsoffers an evaluation of the advancement of the race, the deterrents to that progress, and the opportunities for future advancement as the country entered the twentieth century. Du Bois analyzes the years promptly following the Civil War and, specifically, the Freedmen's Bureau's job in Reconstruction. The Bureau's disappointments were expected not exclusively to southern restriction and national disregard, yet in addition to blunder and courts that were one-sided for dark defendants. The Bureau had victories too, and its most significant commitment to advance was the establishing of African American schools. Since the finish of Reconstruction in 1876, Du Bois claims that the most critical occasion in African American history has been the ascent of the teacher, Booker T. Washington, to the job of representative for the race. Du Bois contends that Washington's way to deal with race relations is counterproductive to the drawn out advancement of the race. Washington's acknowledgment of isolation and his accentuation on material advancement speak to an old disposition of modification and accommodation. Du Bois affirms that this strategy has harmed African Americans by adding to the loss of the vote, the loss of common status, and the loss of help for establishments of advanced education. Du Bois demands that the option to cast a ballot, municipal equity, and the training of youth as per capacity are basic for African American advancement. Du Bois relates his encounters as a teacher in country Tennessee, and afterward he directs his concentration toward a scrutinize of American realism in the rising city of Atlanta where the determined regard for picking up riches takes steps to supplant every single other thought. As far as training, African Americans ought not be instructed only to acquire cash. Or maybe, Du Bois contends there ought to be a harmony between the measures of lower preparing and the principles of human culture and grandiose goals of life. essentially, the African American school should prepare the Gifted Tenth who can thusly add to bring down instruction and furthermore go about as contacts in improving race relations. Du Bois comes back to an assessment of provincial African American existence with an introduction of Dougherty County, Georgia as illustrative of life in the southern Black Belt. He presents the history and current states of the district. Cotton is as yet the life-blood of the Black Belt economy, and scarcely any African Americans are getting a charge out of any monetary achievement. Du Bois portrays the lawful framework and inhabitant cultivating framework as just marginally expelled from subjection. He additionally looks at African American religion from its roots in African culture, through its improvement in bondage, to the development of the Baptist and Methodist houses of worship. He contends that the investigation of Negro religion isn't just a crucial piece of the historical backdrop of the Negro in America, however no uninteresting piece of American history. He proceeds to inspect the effect of bondage on profound quality. In the last parts of his book, Du Bois focuses on how racial partiality impacts people. He grieves the loss of his child, however he thinks about whether his child isn't in an ideal situation dead than experiencing childhood in a world overwhelmed by the shading line. Du Bois relates the account of Alexander Crummel, who battled against bias in his endeavors to turn into an Episcopal minister. In Of the Coming of John, Du Bois presents the account of a youthful dark man who accomplishes training. John's new information, be that as it may, places him at chances with a southern network, and he is pulverized by prejudice. At long last, Du Bois finishes up his book with an exposition on African American spirituals. These melodies have created from their African roots into incredible articulations of the distress, torment, and outcast that describe the African American experience. For Du Bois, these melodies exist not just as the sole American music,

The Changing Role of Women in Society

Changing Role of Women in Society How was the status of lady and their privileges spoken to in western culture in the 1600 to mid twentieth century? For quite a long time, lady and their privileges have been mistreated by the strength of man. There has been proceeded with battle for the acknowledgment of woman’s social jobs and accomplishments, and for their social and political rights. It was a lot of a man centric culture for lady, which impeded or kept lady from understanding their profitable and innovative possibilities.These thoughts where found in the play Merchant of Venice composed by William Shakespeare in c. 1598 when Portia and Nerissa need to take on the appearance of men so they can go into the court to help Antonio in light of the fact that lady are not permitted to enter courts alongside numerous other open spots men had considered unbefitting for lady. Portia says, â€Å"And wear my knife with a more intrepid beauty and talk between the difference in man and k id with a reed voice, and transform two mincing strides into a masculine step, and discuss fights. Another case of this in the Merchant of Venice is when Portia is conversing with Nerissa about the injustice of her dads will, she says â€Å" I may neither pick who I would nor decline who I loathe; so is the desire of a living little girl checked by the desire of a dead dad. † We see this sort of portrayal of lady once more, after 50 years, from my source ‘The Law’s Resolutions of Woman’s Rights, 1632. A case of this can be found in the segment ‘Sect. viii. that the spouse that is his own. It states, â€Å"The spouse hath in that no seisin at all.If anything when he is hitched be given him, he taketh it without anyone else unmistakably to himself,† and that â€Å"the very products which a man giveth to his better half are as yet his own: her chain, her wristbands, her clothing, are largely the acceptable man’s merchandise, †¦ A wif e how gallent soever she be, glistereth however in the wealth of her significant other, as the moon hath no light yet it is the sun’s†¦Ã¢â‚¬  We see proof of this treatment of lady again in this source under the Sect. ix. That which the wide hath is the husband’s. It states â€Å"For in this way it is, if before marriage the lady were equipped with ponies, flawless, sheep, corn, fleece, cash, plate, nd gems, all way of moveable substance is by and by combination the husband’s. † Moving forward in time one more century, we find in my source British Woman’s Emancipation since the Renaissance, in the mid 1800s. It cites from The Times, because of the proposition of a select board of trustees to be set up to consider how to adjust a segment of the Strangers’ Gallery for Ladies’ Gallery in the new House of Commons, The Times opined: â€Å"We should get a kick out of the chance to see a rundown of women who have looked for this metho d of killing their time†¦ As to their quality humanizing banter, it is all fudge.The most fierce scene we at any point saw was in the House of Lords, in expansive day, when the seats were filled women in all the overwhelming attractions of full dress†¦ blood would have been shed in the event that it has still been custom to wear swords†¦ If women of England want this novel method of disposing of their boredom, let them be reveled, yet let us not be so ludicrous as to expect and effect on the character of the discussion. The female audience members might be vulgarize; the male speakers won't be refined. † Finally, I arrive at the time of the Second World War in the mid twentieth century.This prompted a visual promotion marked, Rosie the Riveter. I utilized a critique by Jessica Valenti called Rosie the Riveter leaves a solid heritage to discover data from this banner. It clarifies the foundation of the ad expressing, â€Å"The banner appointed to help enlist lad ies to work during the Second World War. US ladies had consistently worked, obviously, yet the wartime get the opportunity to-work purposeful publicity was explicitly equipped towards white working class ladies, and during the war the female workforce developed by 6. million. † Though this was an immense change from what lady were utilized to, we despite everything see cliché thinking toward the lady, for instance, in one of the ads discharged it says, â€Å"Can you utilize an electric blender? Provided that this is true, at that point you can figure out how to work a drill. † I accept that ladies, truly, have persistently needed to battle for acknowledgment under the strength of man not simply during the 1600s to mid twentieth century yet additionally for a considerable length of time earlier.They have over and again been denied of the natural option to cast a ballot, get a sufficient instruction, and to get the opportunity to create to their fullest human potential. I accept that the view society has on lady is very nearly somewhat of a mystery. My thinking for this is on the grounds that society accepts ladies are less shrewd than men, and along these lines are not equipped for being associated with employments the remainder of society does, they tell lady that they are not permitted to get legitimate training like the remainder of society.This implies that paying little mind to the regular knowledge of a lady, they will never arrive at a similar degree of insight as men since they are not being permitted sufficient instruction so they can create to their full human potential. I accept that the occasions that happened in the eighteenth century were significant later on bearing current women's activist gatherings would take. In spite of the fact that the occasions that occurred during the 1800s was the main trace of progress we saw, it took one more century and a gigantic overall occasion, World War 2, to truly get the show on the road as far a s women's activist campaigning and making genuine long haul change.In my sentiment, the explanation ladies and their privileges in western culture had for all intents and purposes no critical change for larger part of the 400 years I have contemplated is on the grounds that ladies had at no other time gotten the chance to have a go at occupations that had consistently been for men like we saw during the subsequent World War. I accept this is the explanation behind ladies to out of nowhere start a colossal push in women’s rights and correspondence over the most recent 100 years. What started any adjustment in the status of lady and their privileges in western society?As found in my first inquiry, during World War II we started to see huge a move in the job of lady in western culture from housewife to common laborers. At the point when the men came back from war they started to understand that things were changing, the lady had started to have some involvement with the board an d processing plants, which are generally dominatingly male overwhelmed employments. Starting there on we saw a great deal of strain among men and lady which at that point began quick change in the status of lady in contemporary western society.A source that was discharge two decades later that I found had a section to play in the change that had started during the mid-1900s was Betty Freidan’s true to life book, Feminine Mystique, distributed in 1963. In 1957, Freiden was approached to lead a study on the lady at her fifteenth commemoration with her Smith College cohorts. From this study she found that a significant number of her old cohorts were discontent with their lives as housewives, which prompted her to compose the book.The Feminine Mystique was composed from studies and meetings done by Freiden and is broadly viewed as one of the primary components engaged with starting the ‘second wave’ woman's rights in the United States. She expresses that ‘the p ublication choices concerning woman’s magazines were being made for the most part by men, who demanded stories and articles that indicated lady as either cheerful housewives or troubled, hypochondriac careerists, along these lines making the ‘feminine mystic’ †the possibility that lady were normally satisfied by committing their lives to being housewives and moms. I found that was had a tremendous job in the ‘second wave’ as they call it, which started to start enormous change in the status of lady and their privileges in contemporary western culture was the Title VII of the 1964 Civil Rights Act, restricting business separation based on sex just as race, religion, and national cause. The word ‘sex’ was incorporated absolute last minute.Section 703 (a) made it unlawful for a business to â€Å"fail or decline to enlist or to release any individual, or in any case to oppress any person concerning his remuneration, terms, conditions o r benefits or work, in view of such person's race, shading, religion, sex, or national cause. † Another 2 years on, in 1966, 28 ladies and men going to the Third National Conference of the Commission on the Status of Women established an association in Washington, D. C. The association called the National Organization of Women attempts to make sure about political, proficient, and instructive correspondence for woman.In an announcement discharged by Betty Freiden, creator of Feminine Mystique and one of the originators of The National Organization of Woman’s, says that â€Å"The National Organization of Woman is devoted to the relational word that ladies, above all else, are individuals, who, similar to every single others in our general public, must get the opportunity to build up their fullest human potential. We accept that lady can accomplish such balance just by tolerating to the full the difficulties and duties they share with every single others in our general p ublic as a feature of the dynamic standard of American political, conomic and public activity. † In the previous century, society has started to see an inescapable move in the jobs of ladies in contemporary western culture. Critical occasions have occurred in the previous 50 years, which have formed the course of present day woman's rights today. I found that there were many critical occasions that were engaged with starting change in the status of ladies and their privileges in western. In saying this there were unquestionably double cross periods which exposed the disparities in the treatment of ladies, these double cross periods are called first-wave and second

How to Design a Kanban Board (and Get More Work Done)

How to Design a Kanban Board (and Get More Work Done) Over the years, many tools have been developed specifically for work optimization purposes. Some worked, some didn’t, while others were situated somewhere in the middle, meaning they only work under certain circumstances, when subjected to certain variables. Of course, as technology became more advanced and people found ways to integrate it into their work management methodologies, more of these types of tools have come about.The Kanban Board is certainly one of these tools, adhering to the principles of the Kanban method. Again, just like any other work optimization tool, it does not work for everyone. But that is one good thing about these tools. They can be designed and redesigned in such a way that will apply to specific situations. © Shutterstock.com | astephanIn this guide, you willl learn 1) what the Kanban method is, 2) what are the basic principles and characteristics of Kanban, 3) about the benefits of the Kanban method for software development, and 4) how to design a Kanban board.THE KANBAN METHODBut first, we have to gain a better understanding of Kanban. The term kanban is a Japanese word that literally means a “billboard” or a “signboard”. It was formulated by Taiichi Ohno of Toyota as a scheduling system for purposes of inventory control, adhering to the principles of lean manufacturing and just-in-time manufacturing.Software development, in particular, often leans heavily on Kanban as a visual process management system, since it also applies some of the principles of lean manufacturing. That is why we now have the Kanban methodology, which was developed by David Anderson in his attempt to come up with a scientific way to manage or handle work in software development in a way that will not ov erload members of the team with too much work. It puts a lot of focus on the concept of just-in-time delivery, putting a limit on work in progress as the members of a team get their work from a queue or line-up of tasks.Team workflow is a key consideration in this methodology, as it promotes collaboration among members of a team and an organization on a continuous basis. It also encourages continuous and ongoing learning in order to facilitate the idea of self-managed teams.Imagine a software development organization with more than a dozen delivery teams. Without a semblance of order or system to be followed, they are likely to have their priorities crossed and end up overlapping each other. The result is a chaotic environment that, in all likelihood, will affect the delivery of the work and its overall quality. With the Kanban method, order is restored because priorities are made clear.It is also a given that, in any work flow or work process, there are bound to be snags or issues that may crop up. The problem is that, more often than not, these problems are often kept under wraps or go unnoticed. The Kanban method offers a way to reveal these problems, so they can be solved or addressed promptly.Although Anderson developed this methodology purposefully for software development processes, it has come in handy in other areas, such as sales and marketing, human resources management, procurement and logistics, and audit and finance, among others.[slideshare id=41198939doc=10yearsofkanban-141106042748-conversion-gate01w=640h=330]4 BASIC PRINCIPLES OF THE KANBAN METHODAn important statement in the Kanban method goes: “Stop starting and start finishing”. It does make sense, because it is a fact that many teams keep starting tasks or processes even without finishing what they are working on. The most probable result is a pile of unfinished projects â€" a sure sign of inefficiency and lack of effectiveness. Kanban advocates finishing a task before getting started on a new one.The Kanban methodology is rooted in the following principles:This methodology starts with existing processes and roles. Instead of prescribing a specific set of processes, roles, or steps, the Kanban method visualizes the actual workflow or system already in place. In other words, it works with what is already there, and it is just a matter of implementing or stimulating changes.Changes are implemented continuously, and in increments, thereby limiting the amount of work in progress (WIP). This is so that work and work flow is balanced, and the teams do not commit to doing more work than they can handle at one time. This also means that the process is evolving, as opposed to introducing changes drastically, all at once. Workflow is enhanced, because the moment one task is finished, focus is moved on to the next item or task on the priority list.Current processes, roles and responsibilities are respected. Within teams and organizations, there is an underlying apprehensio n whenever the subject of change comes up. If a new system is about to be introduced, or change is sought to be implemented, there is a fear that it may have an adverse impact on individual job titles and the roles and responsibilities that come attached with them.  It also adds a sense of uncertainty with the current way that things are done. Kanban agrees to respect these current roles, processes, responsibilities and job titles, because it recognizes the fact that there are certainly some things that are working very well, so there is no need to change them or eliminate them completely.Kanban method encourages leadership roles to be taken seriously at all levels. Even individual contributors are encouraged to lead, instead of leaving all the leadership actions to senior and top management. Kanban strongly advocates collaboration, which means that even leadership is a collaborative effort.CHARACTERISTICS OF THE KANBAN METHODOLOGYAll too often, many have perceived the Kanban approa ch as something very similar to Scrum. Granted, Scrum also promotes close collaboration and team self-management.However, there are marked differences that we simply cannot ignore.It utilizes single piece flow. Unlike the batch system in Scrum, the Kanban method has team members pull work through the system one at a time. Once one work is done, the next is worked on next.Work and delivery of features is continuous. Scrum has what you call as sprints, something that Kanban does not have. Instead, it works around the idea of continuous delivery. This means that changes may be implemented at any point in time, unlike in Scrum, where changes cannot be implemented when a sprint is in progress.There are no prescribed roles in Kanban. As stated earlier, leadership is present in all levels, so there are no pre-defined roles or distinctions on who the leader is from the members. In Scrum, however, there is a Scrum master distinct from the team members and the product owner.BENEFITS OF KANBAN METHOD IN SOFTWARE DEVELOPMENTIt ensures faster delivery of features. Since the cycle times are short, it increases the likelihood of delivering features more quickly.It improves responsiveness to change, especially in organizations where priorities change frequently.It puts the customers’ preferences first, since it can easily switch things around in accordance with the former’s demands.It is easy to get started, as there is no need for too many setup or installations.It reduces waste and redundancies. Activities that do not add value can be dispensed with so the team can focus on the important tasks.It offers more open lines communication and feedback, making it easier to motivate and empower members of the team.It is easier to understand, because it “paints a picture” of the work and its flow, in contrast to having to wade through pages and pages of wordy documentation. Visual representations, after all, stick faster and longer, than written text.So what determines wheth er an organization should follow the Kanban methodology or look for another method for its work optimization? In-depth study must be performed to determine whether Kanban is a good fit for the organization or not. The key determinants are the organizational structure, culture, and the team dynamics currently in force within the organization.But there can be also some problems with introducing Kanban into a business as discussed in this video. THE KANBAN BOARDYou were able to get to know the method, but how do you apply it? For that, you will need tools, and one of the most commonly used tools to implement the Kanban method is the Kanban board.The kanban board is basically a work and workflow visualization tool with the specific purpose of aiding organizations in optimizing the flow of work.Traditionally, the tools used were signal cards, aptly called kanban cards. When they took on the form of physical kanban boards, they may be drawn on a whiteboard, a blackboard, or even on the wa ll. They also make use of items such as magnets, plastic chips, tokens, or index cards. The most preferred and most commonly used, however, are sticky notes.Nowadays, we also have online kanban boards, which is certainly more convenient for those who prefer working on computers.[slideshare id=19102981doc=kanbanboardsimulation-0-1-130418152140-phpapp02w=640h=330]DESIGNING A KANBAN BOARDThe design of the kanban board will primarily depend on the type of processes that the organization implements. Most assuredly, the design of the kanban board of a manufacturing company will be different from that of a software development company.Normally, a manufacturing company will have a kanban board that is divided into three parts:Awaiting productionWork in progressCompleted workIn simplest terms, these three sections may also be labeled as “To Do Tasks”, “Current Tasks”, and “Completed Tasks”.The operations of software developments teams fall under the complex category, which is why you are likely to find the following areas or sections in their kanban board:Backlog, which is basically a backlog of stories, often integrated with the pre-plan or things to be done by the developer, in accordance with the demands of the customer or product ownerReady, where works that are ready for development are under. This is where team members can pull work from when they are free.Development tasks, or work items, which may be further broken down into the specific tasks. Examples are Coding, Awaiting Testing, Testing, Approval or Ready for Deployment.Done, which contains the completed works.Now, depending on the preferences of the team, you may use a physical kanban board or an online or virtual one. Again, it really depends on what the team is most comfortable with. Designing the Kanban board is a process in itself, and the steps are as follows:#1 Visualize and map the flow of workYou have to visualize and map out the process that is being followed to complete work. This wil l give you â€" and everyone in the organization, not just the members of the team â€" more than a glimpse of the whole process. This way, they will be knowledgeable about all its aspects, so they can contribute more. This will also be useful in monitoring the progress of work of a team.Use kanban cards or sticky notes to represent the work that will be done. If the processes are simple enough, mapping it out should be just as simple, with straight vertical lines down the board. However, in the event that the processes are quite complex, it may require both vertical and horizontal lines, often intersecting each other at some points.Sticky notes are preferred because of the flexibility that they offer. For example, color coded sticky notes may refer to specific works. Green cards may represent a specific feature that needs to be worked on, while a blue one may represent another.The colors may also represent the level of priority of the work. Red sticky notes can represent high priorit y works or those that require the most urgency. Once team members spot these cards, they will pull it out because they require the highest priority.The notes may then be pulled out and transferred from one area or section of the board to another, as appropriate.One rule of thumb is that the lanes or columns are often verbs or verb phrases (e.g. TO DO, DOING, IN WORK) since they pertain to the activities to be performed by members of the team, while the cards or notes contain nouns or noun phrases (e.g. FEATURE, WORK), since they are the things that must be delivered by the team.Another great presentation that walks you through building your Kanban Board.[slideshare id=55766609doc=module8-kanbanboarddesign-151203043514-lva1-app6892w=640h=330]#2 Set initial limits on your work in progressWe have mentioned earlier that one of the benefits of using the Kanban method is that work in progress becomes limited. When designing your kanban board, you have to set initial work in progress limit s, meaning, at any point in time, the “CURRENT”, “WIP”, “IN PROGRESS” or “IN WORK” section (depending on what title or label you have chosen) should have only a maximum number of sticky notes.For example, the team has decided to limit the number of works in progress to only three. This means that at no point should the number of sticky notes on the WIP section exceed three. This means that the only time that a new piece of work (or sticky note) will be placed on the WIP section is after one sticky note has been pulled out, worked on, and moved to the COMPLETED or DONE section.This is so that the team will avoid having too much work in progress. Again, remember the statement: Stop starting and start finishing. You must finish the current works in progress first before starting a new one.Learn more about setting WIP limits and scheduling work from David Anderson. #3 Get your works in progress on the boardThe first thing you should do is to identify all the works that a re currently being worked on. Once you have done that and you find that they have exceeded the limits you have initially set for your WIP, it is time to prioritize the works in progress on your list.If your team has identified six current works in development, rank them accordingly in order of importance or urgency. If you have initially set 3 WIP as your limits, choose the top three. Once they have been moved to the next lane or task, add the next WIP on your list to the lane.#4 Inspect and adapt, then improveAll throughout the process, you should monitor closely, so you can immediately adapt and effect changes, if and when necessary. This is also the part where you have to actively look for bottlenecks and any possible hidden work in progress. Yes, it is possible that you are working on, or waiting on, a work in progress that was not put on the board. This is why it is important to make sure you have identified all your works in progress,This will also allow you to make improvemen ts. Keep in mind that improvement should be done collaboratively. This is especially true when parallel workflows are involved and there are multiple value streams, often in the form of teams working with other teams.We have only discussed a simple kanban board design. Of course, this will not apply in all cases, especially those teams that have complex works and processes. For that, the kanban board design will be decidedly more complicated.Keep in mind that the kanban board is not limited to software development processes only. It may also be designed for use in different contexts or settings, including system administration, business process operations and maintenance, customer service and support, sales and marketing. Always be mindful of the nature of business processes when you go about designing your kanban board.

Human Nature, The Good Life, Its Importance Of Rhetoric

Name: Professor: Course: Date: Human Nature, the Good Life, Its Importance to Rhetoric in Aristotle’s Rhetoric Introduction Rhetoric is an art of communication that aims at enhancing the capability of writers or speakers who endeavor to persuade, inform or inspire distinct audiences in exceptional scenarios. As a discipline of recognized teaching and a prolific civic application, rhetoric has played a fundamental role in the Western convention. Rhetoric is acknowledged best from the description of Aristotle who regards it as a compliment of both politics and logic, and terms it as the ability to make an observation in any given instance from the accessible means of influence. Unlike other Aristotle works that have been around for ages,†¦show more content†¦Therefore, in political rhetoric, the discussion is whether the suggestion is outstanding or detrimental. The trial lawyers have arguments over whatever is fair or unfair and the display rhetoric is concerned with the shame or honor. In deliberating for whatever is convenient, the political presenters may perhaps disregard whether it is unjust or not. Complainants may not refute that something has occurred or that it has a basis for damage; nevertheless they will not confess that their client is culpable of prejudice (James 211). Rhetorical suggestions may be complete evidences, indications, or possibilities. Political rhetoric incorporates the ethical and logic branch of politics. Aristotle defined the five main disciplines of political rhetoric as techniques and means, peace and war, national security, legislation, and trade. Consequently, the presenter must be conscious of the revenue source of the state and the expenditures, the strength of the armed forces of the nation and its foes, the installations and means of security, the food supply sources and requirements, as well as, the exports and imports, ascertaining the country does not upset the superior states and partners of trade, laws and constitution of the state, the developments that are internal, and in acknowledging the conventions of additional states’ history are valuable. Rhetoric can provoke emotions that may perhaps not be connected to the fundamental facts.Show MoreRelatedPlato and Aristotles Impact on Rhetoric1503 Words   |  7 Pagesrhetoricians than had a great impact on the history of rhetoric. Although they were similar in many ways, their use and definition of rhetoric were different. Plato had the more classical approach where he used rhetoric as a means of education to pass down his beliefs and practice of rhetoric to his students. 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According to Aristotle, persuasionRead MoreWealth of Nations1626 Words   |  7 PagesMichelle Trejo Dr. King Human Nature and the Social Order II June 6, 2008 â€Å"The Wealth of Nations† Adam Smith, the author of â€Å"The Wealth of Nations†, was a Scottish moral philosopher during the Industrial Revolution who was inspired by his surroundings to write about the field of economics. Being a man of intellect on various types of philosophical views, Smith was able to portray his passionate feelings about political thought through his well-written works. While publishing his book, Smith becameRead MoreAnalysis Of Gorgias Encomium Of Helen, Isocrates, And Plato s Gorgias1316 Words   |  6 PagesOne of the main differences between humans and animals is our stream of conscience. Our stream of conscience contributes to our ability to speak and form language in a powerful way, which overall contributes to the ability to function successfully within a society. Many philosophers built on the philosophies of the political atmosphere, language, and the shift from literacy (recited knowledge) to oratory (agency, ability to formulate personal thoughts and opinions). Through the analysis of variousRead MoreAnalysis Of Encomium Of Helen, Dissoi Logoi, And Plato s Gorgias1541 Words   |  7 PagesIntroduction One of the main differences between humans and animals is our stream of conscience. Our stream of conscience contributes to our ability to speak and form language in a powerful way, which overall contributes to the ability to function successfully within a society. Many philosophers built on the philosophies of the political atmosphere, language, and the shift from literacy (recited knowledge) to oratory (agency, ability to formulate personal thoughts and opinions). Through the analysisRead MoreGod Is A Problem Of Failure1367 Words   |  6 PagesAs humans, we are so focused on sin. It is innate in us, and it overpowers us. We are so caught in our failure and wrong doings that we forget what we are doing right, often avoiding a relationship with the one who created us and made us who we are today. Everyone wonders why we die, but the simple answer can be found in the bible-sin. You may think sin leads to failure, and failure leads to death, but that is not the case. It may seem like there is no escape to avoid death, but there is. God hasRead MoreRhetoric In Boy I n The Striped Pajamas1246 Words   |  5 Pagesespecially when it comes to the aspect of race. In The Boy in the Striped Pajamas, the power of rhetoric is shown in the culture between the German’s and the Jew’s lives and the importance in the little boy’s love toward the other side of the fence. The message in The Boy in the Striped Pajamas indicates the significance of life. The German and Jewish cultures shouldn’t define the importance of an individual’s life. However, during the German War it was exactly what was happening. 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Academic Background Essay Samples - Is it a Scam?

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Open Domain Event Extraction from Twitter Free Essays

string(212) " approaches to event categorization would require \? st designing annotation guidelines \(including selecting an appropriate set of types to annotate\), then annotating a large corpus of events found in Twitter\." Open Domain Event Extraction from Twitter Alan Ritter University of Washington Computer Sci. Eng. Seattle, WA aritter@cs. We will write a custom essay sample on Open Domain Event Extraction from Twitter or any similar topic only for you Order Now washington. edu Mausam University of Washington Computer Sci. Eng. Seattle, WA mausam@cs. washington. edu Oren Etzioni University of Washington Computer Sci. Eng. Seattle, WA etzioni@cs. washington. edu Sam Clark? Decide, Inc. Seattle, WA sclark. uw@gmail. com ABSTRACT Tweets are the most up-to-date and inclusive stream of information and commentary on current events, but they are also fragmented and noisy, motivating the need for systems that can extract, aggregate and categorize important events. Previous work on extracting structured representations of events has focused largely on newswire text; Twitter’s unique characteristics present new challenges and opportunities for open-domain event extraction. This paper describes TwiCal— the ? rst open-domain event-extraction and categorization system for Twitter. We demonstrate that accurately extracting an open-domain calendar of signi? cant events from Twitter is indeed feasible. In addition, we present a novel approach for discovering important event categories and classifying extracted events based on latent variable models. By leveraging large volumes of unlabeled data, our approach achieves a 14% increase in maximum F1 over a supervised baseline. A continuously updating demonstration of our system can be viewed at http://statuscalendar. com; Our NLP tools are available at http://github. com/aritter/ twitter_nlp. Entity Steve Jobs iPhone GOP Amanda Knox Event Phrase died announcement debate verdict Date 10/6/11 10/4/11 9/7/11 10/3/11 Type Death ProductLaunch PoliticalEvent Trial Table 1: Examples of events extracted by TwiCal. vents. Yet the number of tweets posted daily has recently exceeded two-hundred million, many of which are either redundant [57], or of limited interest, leading to information overload. 1 Clearly, we can bene? t from more structured representations of events that are synthesized from individual tweets. Previous work in event extraction [21, 1, 54, 18, 43, 11, 7] has focused largely on news articles, as historically this genre of text has been the best source of information on curr ent events. Read also Twitter Case Study In the meantime, social networking sites such as Facebook and Twitter have become an important complementary source of such information. While status messages contain a wealth of useful information, they are very disorganized motivating the need for automatic extraction, aggregation and categorization. Although there has been much interest in tracking trends or memes in social media [26, 29], little work has addressed the challenges arising from extracting structured representations of events from short or informal texts. Extracting useful structured representations of events from this disorganized corpus of noisy text is a challenging problem. On the other hand, individual tweets are short and self-contained and are therefore not composed of complex discourse structure as is the case for texts containing narratives. In this paper we demonstrate that open-domain event extraction from Twitter is indeed feasible, for example our highest-con? dence extracted future events are 90% accurate as demonstrated in  §8. Twitter has several characteristics which present unique challenges and opportunities for the task of open-domain event extraction. Challenges: Twitter users frequently mention mundane events in their daily lives (such as what they ate for lunch) which are only of interest to their immediate social network. In contrast, if an event is mentioned in newswire text, it 1 http://blog. twitter. com/2011/06/ 200-million-tweets-per-day. html Categories and Subject Descriptors I. 2. 7 [Natural Language Processing]: Language parsing and understanding; H. 2. [Database Management]: Database applications—data mining General Terms Algorithms, Experimentation 1. INTRODUCTION Social networking sites such as Facebook and Twitter present the most up-to-date information and buzz about current ? This work was conducted at the University of Washington Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro? t or commercial advantage and that copies bear this notice and the full citation on the ? rst page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speci? c permission and/or a fee. KDD’12, August 12–16, 2012, Beijing, China. Copyright 2012 ACM 978-1-4503-1462-6 /12/08 †¦ $10. 00. is safe to assume it is of general importance. Individual tweets are also very terse, often lacking su? cient context to categorize them into topics of interest (e. g. Sports, Politics, ProductRelease etc†¦ ). Further because Twitter users can talk about whatever they choose, it is unclear in advance which set of event types are appropriate. Finally, tweets are written in an informal style causing NLP tools designed for edited texts to perform extremely poorly. Opportunities: The short and self-contained nature of tweets means they have very simple discourse and pragmatic structure, issues which still challenge state-of-the-art NLP systems. For example in newswire, complex reasoning about relations between events (e. g. before and after ) is often required to accurately relate events to temporal expressions [32, 8]. The volume of Tweets is also much larger than the volume of news articles, so redundancy of information can be exploited more easily. To address Twitter’s noisy style, we follow recent work on NLP in noisy text [46, 31, 19], annotating a corpus of Tweets with events, which is then used as training data for sequence-labeling models to identify event mentions in millions of messages. Because of the terse, sometimes mundane, but highly redundant nature of tweets, we were motivated to focus on extracting an aggregate representation of events which provides additional context for tasks such as event categorization, and also ? lters out mundane events by exploiting redundancy of information. We propose identifying important events as those whose mentions are strongly associated with references to a unique date as opposed to dates which are evenly distributed across the calendar. Twitter users discuss a wide variety of topics, making it unclear in advance what set of event types are appropriate for categorization. To address the diversity of events discussed on Twitter, we introduce a novel approach to discovering important event types and categorizing aggregate events within a new domain. Supervised or semi-supervised approaches to event categorization would require ? st designing annotation guidelines (including selecting an appropriate set of types to annotate), then annotating a large corpus of events found in Twitter. You read "Open Domain Event Extraction from Twitter" in category "Papers" This approach has several drawbacks, as it is apriori unclear what set of types should be annotated; a large amount of e? ort would be required to manually annotate a corpus of ev ents while simultaneously re? ning annotation standards. We propose an approach to open-domain event categorization based on latent variable models that uncovers an appropriate set of types which match the data. The automatically discovered types are subsequently inspected to ? lter out any which are incoherent and the rest are annotated with informative labels;2 examples of types discovered using our approach are listed in ? gure 3. The resulting set of types are then applied to categorize hundreds of millions of extracted events without the use of any manually annotated examples. By leveraging large quantities of unlabeled data, our approach results in a 14% improvement in F1 score over a supervised baseline which uses the same set of types. Stanford NER T-seg P 0. 62 0. 73 R 0. 5 0. 61 F1 0. 44 0. 67 F1 inc. 52% Table 2: By training on in-domain data, we obtain a 52% improvement in F1 score over the Stanford Named Entity Recognizer at segmenting entities in Tweets [46]. 2. SYSTEM OVERVIEW TwiCal extracts a 4-tuple representation of events which includes a named entity, event phrase, calendar date, and event type (see Table 1). This representation was chosen to closely match the way import ant events are typically mentioned in Twitter. An overview of the various components of our system for extracting events from Twitter is presented in Figure 1. Given a raw stream of tweets, our system extracts named entities in association with event phrases and unambiguous dates which are involved in signi? cant events. First the tweets are POS tagged, then named entities and event phrases are extracted, temporal expressions resolved, and the extracted events are categorized into types. Finally we measure the strength of association between each named entity and date based on the number of tweets they co-occur in, in order to determine whether an event is signi? cant. NLP tools, such as named entity segmenters and part of speech taggers which were designed to process edited texts (e. g. news articles) perform very poorly when applied to Twitter text due to its noisy and unique style. To address these issues, we utilize a named entity tagger and part of speech tagger trained on in-domain Twitter data presented in previous work [46]. We also develop an event tagger trained on in-domain annotated data as described in  §4. 3. NAMED ENTITY SEGMENTATION NLP tools, such as named entity segmenters and part of speech taggers which were designed to process edited texts (e. g. ews articles) perform very poorly when applied to Twitter text due to its noisy and unique style. For instance, capitalization is a key feature for named entity extraction within news, but this feature is highly unreliable in tweets; words are often capitalized simply for emphasis, and named entities are often left all lowercase. In addition, tweets contain a higher proportion of out -ofvocabulary words, due to Twitter’s 140 character limit and the creative spelling of its users. To address these issues, we utilize a named entity tagger trained on in-domain Twitter data presented in previous work [46]. Training on tweets vastly improves performance at segmenting Named Entities. For example, performance compared against the state-of-the-art news-trained Stanford Named Entity Recognizer [17] is presented in Table 2. Our system obtains a 52% increase in F1 score over the Stanford Tagger at segmenting named entities. 4. EXTRACTING EVENT MENTIONS This annotation and ? ltering takes minimal e? ort. One of the authors spent roughly 30 minutes inspecting and annotating the automatically discovered event types. 2 In order to extract event mentions from Twitter’s noisy text, we ? st annotate a corpus of tweets, which is then 3 Available at http://github. com/aritter/twitter_nlp. Temporal Resolution S M T W T F S Tweets POS Tag NER Signi? cance Ranking Calend ar Entries Event Tagger Event Classi? cation Figure 1: Processing pipeline for extracting events from Twitter. New components developed as part of this work are shaded in grey. used to train sequence models to extract events. While we apply an established approach to sequence-labeling tasks in noisy text [46, 31, 19], this is the ? rst work to extract eventreferring phrases in Twitter. Event phrases can consist of many di? erent parts of speech as illustrated in the following examples: †¢ Verbs: Apple to Announce iPhone 5 on October 4th?! YES! †¢ Nouns: iPhone 5 announcement coming Oct 4th †¢ Adjectives: WOOOHOO NEW IPHONE TODAY! CAN’T WAIT! These phrases provide important context, for example extracting the entity, Steve Jobs and the event phrase died in connection with October 5th, is much more informative than simply extracting Steve Jobs. In addition, event mentions are helpful in upstream tasks such as categorizing events into types, as described in  §6. In order to build a tagger for recognizing events, we annotated 1,000 tweets (19,484 tokens) with event phrases, following annotation guidelines similar to those developed for the Event tags in Timebank [43]. We treat the problem of recognizing event triggers as a sequence labeling task, using Conditional Random Fields for learning and inference [24]. Linear Chain CRFs model dependencies between the predicted labels of adjacent words, which is bene? cial for extracting multi-word event phrases. We use contextual, dictionary, and orthographic features, and also include features based on our Twitter-tuned POS tagger [46], and dictionaries of event terms gathered from WordNet by Sauri et al. [50]. The precision and recall at segmenting event phrases are reported in Table 3. Our classi? er, TwiCal-Event, obtains an F-score of 0. 64. To demonstrate the need for in-domain training data, we compare against a baseline of training our system on the Timebank corpus. precision 0. 56 0. 48 0. 24 recall 0. 74 0. 70 0. 11 F1 0. 64 0. 57 0. 15 TwiCal-Event No POS Timebank Table 3: Precision and recall at event phrase extraction. All results are reported using 4-fold cross validation over the 1,000 manually annotated tweets (about 19K tokens). We compare against a system which doesn’t make use of features generated based on our Twitter trained POS Tagger, in addition to a system trained on the Timebank corpus which uses the same set of features. as input a reference date, some text, and parts of speech (from our Twitter-trained POS tagger) and marks temporal expressions with unambiguous calendar references. Although this mostly rule-based system was designed for use on newswire text, we ? d its precision on Tweets (94% estimated over as sample of 268 extractions) is su? ciently high to be useful for our purposes. TempEx’s high precision on Tweets can be explained by the fact that some temporal expressions are relatively unambiguous. Although there appears to be room for improving the recall of temporal extraction on Twitter by handling no isy temporal expressions (for example see Ritter et. al. [46] for a list of over 50 spelling variations on the word â€Å"tomorrow†), we leave adapting temporal extraction to Twitter as potential future work. . CLASSIFICATION OF EVENT TYPES To categorize the extracted events into types we propose an approach based on latent variable models which infers an appropriate set of event types to match our data, and also classi? es events into types by leveraging large amounts of unlabeled data. Supervised or semi-supervised classi? cation of event categories is problematic for a number of reasons. First, it is a priori unclear which categories are appropriate for Twitter. Secondly, a large amount of manual e? ort is required to annotate tweets with event types. Third, the set of important categories (and entities) is likely to shift over time, or within a focused user demographic. Finally many important categories are relatively infrequent, so even a large annotated dataset may contain just a few examples of these categories, making classi? cation di? cult. For these reasons we were motivated to investigate un- 5. EXTRACTING AND RESOLVING TEMPORAL EXPRESSIONS In addition to extracting events and related named entities, we also need to extract when they occur. In general there are many di? rent ways users can refer to the same calendar date, for example â€Å"next Friday†, â€Å"August 12th†, â€Å"tomorrow† or â€Å"yesterday† could all refer to the same day, depending on when the tweet was written. To resolve temporal expressions we make use of TempEx [33], which takes Sports Party TV Politics Celebrity Music Movie Food Concert Performance Fitness Interview ProductRelease Meeting Fashion Finance School AlbumRele ase Religion 7. 45% 3. 66% 3. 04% 2. 92% 2. 38% 1. 96% 1. 92% 1. 87% 1. 53% 1. 42% 1. 11% 1. 01% 0. 95% 0. 88% 0. 87% 0. 85% 0. 85% 0. 78% 0. 71% Con? ct Prize Legal Death Sale VideoGameRelease Graduation Racing Fundraiser/Drive Exhibit Celebration Books Film Opening/Closing Wedding Holiday Medical Wrestling OTHER 0. 69% 0. 68% 0. 67% 0. 66% 0. 66% 0. 65% 0. 63% 0. 61% 0. 60% 0. 60% 0. 60% 0. 58% 0. 50% 0. 49% 0. 46% 0. 45% 0. 42% 0. 41% 53. 45% Label Sports Concert Perform TV Movie Sports Politics Figure 2: Complete list of automatically discovered event types with percentage of data covered. Interpretable types representing signi? cant events cover roughly half of the data. supervised approaches that will automatically induce event types which match the data. We adopt an approach based on latent variable models inspired by recent work on modeling selectional preferences [47, 39, 22, 52, 48], and unsupervised information extraction [4, 55, 7]. Each event indicator phrase in our data, e, is modeled as a mixture of types. For example the event phrase â€Å"cheered† might appear as part of either a PoliticalEvent, or a SportsEvent. Each type corresponds to a distribution over named entities n involved in speci? c instances of the type, in addition to a distribution over dates d on which events of the type occur. Including calendar dates in our model has the e? ct of encouraging (though not requiring) events which occur on the same date to be assigned the same type. This is helpful in guiding inference, because distinct references to the same event should also have the same type. The generative story for our data is based on LinkLDA [15], and is presented as Algorithm 1. This approach has the advantage that information about an event ph rase’s type distribution is shared across it’s mentions, while ambiguity is also naturally preserved. In addition, because the approach is based on generative a probabilistic model, it is straightforward to perform many di? rent probabilistic queries about the data. This is useful for example when categorizing aggregate events. For inference we use collapsed Gibbs Sampling [20] where each hidden variable, zi , is sampled in turn, and parameters are integrated out. Example types are displayed in Figure 3. To estimate the distribution over types for a given event, a sample of the corresponding hidden variables is taken from the Gibbs markov chain after su? cient burn in. Prediction for new data is performed using a streaming approach to inference [56]. TV Product Meeting Top 5 Event Phrases tailgate – scrimmage tailgating – homecoming – regular season concert – presale – performs – concerts – tickets matinee – musical priscilla – seeing wicked new season – season ? nale – ? nished season episodes – new episode watch love – dialogue theme – inception – hall pass – movie inning – innings pitched – homered homer presidential debate osama – presidential candidate – republican debate – debate performance network news broadcast – airing – primetime drama – channel stream unveils – unveiled – announces – launches wraps o? shows trading – hall mtg – zoning – brie? g stocks – tumbled – trading report – opened higher – tumbles maths – english test exam – revise – physics in stores – album out debut album – drops on – hits stores voted o? – idol – scotty – idol season – dividendpaying sermon – preaching preached – worship preach declared war – war shelling – opened ? re wounded senate – legislation – repeal – budget – election winners – lotto results enter – winner – contest bail plea – murder trial – sentenced – plea – convicted ? lm festival – screening starring – ? lm – gosling live forever – passed away – sad news – condolences – burried add into – 50% o? up shipping – save up donate – tornado relief disaster relief – donated – raise money Top 5 Entities espn – ncaa – tigers – eagles – varsity taylor swift – toronto britney spears – rihanna – rock shrek – les mis – lee evans – w icked – broadway jersey shore – true blood – glee – dvr – hbo net? ix – black swan – insidious – tron – scott pilgrim mlb – red sox – yankees – twins – dl obama president obama – gop – cnn america nbc – espn – abc – fox mtv apple – google – microsoft – uk – sony town hall – city hall club – commerce – white house reuters – new york – u. . – china – euro english – maths – german – bio – twitter itunes – ep – uk – amazon – cd lady gaga – american idol – america – beyonce – glee church – jesus – pastor faith – god libya – afghanistan #syria – syria – nato senate – house – congress – obama – gop ipad – award – facebook â⠂¬â€œ good luck – winners casey anthony – court – india – new delhi supreme court hollywood – nyc – la – los angeles – new york michael jackson afghanistan john lennon – young – peace groupon – early bird facebook – @etsy – etsy japan – red cross – joplin – june – africa Finance School Album TV Religion Con? ict Politics Prize Legal Movie Death Sale Drive 6. 1 Evaluation To evaluate the ability of our model to classify signi? cant events, we gathered 65 million extracted events of the form Figure 3: Example event types discovered by our model. For each type t, we list the top 5 entities which have highest probability given t, and the 5 event phrases which assign highest probability to t. Algorithm 1 Generative story for our data involving event types as hidden variables. Bayesian Inference techniques are applied to invert the generative process and infer an appropriate set of types to describe the observed events. for each event type t = 1 . . . T do n Generate ? t according to symmetric Dirichlet distribution Dir(? n ). d Generate ? t according to symmetric Dirichlet distribution Dir(? d ). end for for each unique event phrase e = 1 . . . |E| do Generate ? e according to Dirichlet distribution Dir(? ). for each entity which co-occurs with e, i = 1 . . . Ne do n Generate ze,i from Multinomial(? e ). Generate the entity ne,i from Multinomial(? n ). e,i TwiCal-Classify Supervised Baseline Precision 0. 85 0. 61 Recall 0. 55 0. 57 F1 0. 67 0. 59 Table 4: Precision and recall of event type categorization at the point of maximum F1 score. d,i end for end for 0. 6 end for for each date which co-occurs with e, i = 1 . . . Nd do d Generate ze,i from Multinomial(? e ). Generate the date de,i from Multinomial(? zn ). Precision 0. 8 1. 0 listed in Figure 1 (not including the type). We then ran Gibbs Sampling with 100 types for 1,000 iterations of burnin, keeping the hidden variable assignments found in the last sample. One of the authors manually inspected the resulting types and assigned them labels such as Sports, Politics, MusicRelease and so on, based on their distribution over entities, and the event words which assign highest probability to that type. Out of the 100 types, we found 52 to correspond to coherent event types which referred to signi? cant events;5 the other types were either incoherent, or covered types of events which are not of general interest, for example there was a cluster of phrases such as applied, call, contact, job interview, etc†¦ hich correspond to users discussing events related to searching for a job. Such event types which do not correspond to signi? cant events of general interest were simply marked as OTHER. A complete list of labels used to annotate the automatically discovered event types along wi th the coverage of each type is listed in ? gure 2. Note that this assignment of labels to types only needs to be done once and produces a labeling for an arbitrarily large number of event instances. Additionally the same set of types can easily be used to lassify new event instances using streaming inference techniques [56]. One interesting direction for future work is automatic labeling and coherence evaluation of automatically discovered event types analogous to recent work on topic models [38, 25]. In order to evaluate the ability of our model to classify aggregate events, we grouped together all (entity,date) pairs which occur 20 or more times the data, then annotated the 500 with highest association (see  §7) using the event types discovered by our model. To help demonstrate the bene? s of leveraging large quantities of unlabeled data for event classi? cation, we compare against a supervised Maximum Entropy baseline which makes use of the 500 annotated events using 10-fold c ross validation. For features, we treat the set of event phrases To scale up to larger datasets, we performed inference in parallel on 40 cores using an approximation to the Gibbs Sampling procedure analogous to that presented by Newmann et. al. [37]. 5 After labeling some types were combined resulting in 37 distinct labels. 4 0. 4 Supervised Baseline TwiCal? Classify 0. 0 0. 2 0. 4 Recall 0. 0. 8 Figure 4: types. Precision and recall predicting event that co-occur with each (entity, date) pair as a bag-of-words, and also include the associated entity. Because many event categories are infrequent, there are often few or no training examples for a category, leading to low performance. Figure 4 compares the performance of our unsupervised approach to the supervised baseline, via a precision-recall curve obtained by varying the threshold on the probability of the most likely type. In addition table 4 compares precision and recall at the point of maximum F-score. Our unsupervised approach to event categorization achieves a 14% increase in maximum F1 score over the supervised baseline. Figure 5 plots the maximum F1 score as the amount of training data used by the baseline is varied. It seems likely that with more data, performance will reach that of our approach which does not make use of any annotated events, however our approach both automatically discovers an appropriate set of event types and provides an initial classi? er with minimal e? ort, making it useful as a ? rst step in situations where annotated data is not immediately available. . RANKING EVENTS Simply using frequency to determine which events are signi? cant is insu? cient, because many tweets refer to common events in user’s daily lives. As an example, users often mention what they are eating for lunch, therefore entities such as McDonalds occur relatively frequently in association with references to most calendar days. Important events can be distinguished as those whi ch have strong association with a unique date as opposed to being spread evenly across days on the calendar. To extract signi? ant events of general interest from Twitter, we thus need some way to measure the strength of association between an entity and a date. In order to measure the association strength between an 0. 8 0. 2 Supervised Baseline TwiCal? Classify 100 200 300 400 tweets. We then added the extracted triples to the dataset used for inferring event types described in  §6, and performed 50 iterations of Gibbs sampling for predicting event types on the new data, holding the hidden variables in the original data constant. This streaming approach to inference is similar to that presented by Yao et al. 56]. We then ranked the extracted events as described in  §7, and randomly sampled 50 events from the top ranked 100, 500, and 1,000. We annotated the events with 4 separate criteria: 1. Is there a signi? cant event involving the extracted entity which will take place on t he extracted date? 2. Is the most frequently extracted event phrase informative? 3. Is the event’s type correctly classi? ed? 4. Are each of (1-3) correct? That is, does the event contain a correct entity, date, event phrase, and type? Note that if (1) is marked as incorrect for a speci? event, subsequent criteria are always marked incorrect. Max F1 0. 4 0. 6 # Training Examples Figure 5: Maximum F1 score of the supervised baseline as the amount of training data is varied. entity and a speci? c date, we utilize the G log likelihood ratio statistic. G2 has been argued to be more appropriate for text analysis tasks than ? 2 [12]. Although Fisher’s Exact test would produce more accurate p-values [34], given the amount of data with which we are working (sample size greater than 1011 ), it proves di? cult to compute Fisher’s Exact Test Statistic, which results in ? ating point over? ow even when using 64-bit operations. The G2 test works su? ciently well in our setti ng, however, as computing association between entities and dates produces less sparse contingency tables than when working with pairs of entities (or words). The G2 test is based on the likelihood ratio between a model in which the entity is conditioned on the date, and a model of independence between entities and date references. For a given entity e and date d this statistic can be computed as follows: G2 = x? {e, ¬e},y? {d, ¬d} 2 8. 2 Baseline To demonstrate the importance of natural language processing and information extraction techniques in extracting informative events, we compare against a simple baseline which does not make use of the Ritter et. al. named entity recognizer or our event recognizer; instead, it considers all 1-4 grams in each tweet as candidate calendar entries, relying on the G2 test to ? lter out phrases which have low association with each date. 8. 3 Results The results of the evaluation are displayed in table 5. The table shows the precision of the systems at di? rent yield levels (number of aggregate events). These are obtained by varying the thresholds in the G2 statistic. Note that the baseline is only comparable to the third column, i. e. , the precision of (entity, date) pairs, since the baseline is not performing event identi? cation and classi? cation. Although in some cases ngrams do correspond to informative calendar entries, the precision of the ngram baseline is extremely low compared wi th our system. In many cases the ngrams don’t correspond to salient entities related to events; they often consist of single words which are di? ult to interpret, for example â€Å"Breaking† which is part of the movie â€Å"Twilight: Breaking Dawn† released on November 18. Although the word â€Å"Breaking† has a strong association with November 18, by itself it is not very informative to present to a user. 7 Our high-con? dence calendar entries are surprisingly high quality. If we limit the data to the 100 highest ranked calendar entries over a two-week date range in the future, the precision of extracted (entity, date) pairs is quite good (90%) – an 80% increase over the ngram baseline. As expected precision drops as more calendar entries are displayed, but 7 In addition, we notice that the ngram baseline tends to produce many near-duplicate calendar entries, for example: â€Å"Twilight Breaking†, â€Å"Breaking Dawn†, and â€Å"Twilight Breaking Dawn†. While each of these entries was annotated as correct, it would be problematic to show this many entries describing the same event to a user. Ox,y ? ln Ox,y Ex,y Where Oe,d is the observed fraction of tweets containing both e and d, Oe, ¬d is the observed fraction of tweets containing e, but not d, and so on. Similarly Ee,d is the expected fraction of tweets containing both e and d assuming a model of independence. 8. EXPERIMENTS To estimate the quality of the calendar entries generated using our approach we manually evaluated a sample of the top 100, 500 and 1,000 calendar entries occurring within a 2-week future window of November 3rd. 8. 1 Data For evaluation purposes, we gathered roughly the 100 million most recent tweets on November 3rd 2011 (collected using the Twitter Streaming API6 , and tracking a broad set of temporal keywords, including â€Å"today†, â€Å"tomorrow†, names of weekdays, months, etc. ). We extracted named entities in addition to event phrases, and temporal expressions from the text of each of the 100M 6 https://dev. twitter. com/docs/streaming-api Mon Nov 7 Justin meet Other Motorola Pro+ kick Product Release Nook Color 2 launch Product Release Eid-ul-Azha celebrated Performance MW3 midnight release Other Tue Nov 8 Paris love Other iPhone holding Product Release Election Day vote Political Event Blue Slide Park listening Music Release Hedley album Music Release Wed Nov 9 EAS test Other The Feds cut o? Other Toca Rivera promoted Performance Alert System test Other Max Day give Other November 2011 Thu Nov 10 Fri Nov 11 Robert Pattinson iPhone show debut Performance Product Release James Murdoch Remembrance Day give evidence open Other Performance RTL-TVI France post play TV Event Other Gotti Live Veterans Day work closed Other Other Bambi Awards Skyrim perform arrives Performance Product Release Sat Nov 12 Sydney perform Other Pullman Ballroom promoted Other Fox ? ght Other Plaza party Party Red Carpet invited Party Sun Nov 13 Playstation answers Product Release Samsung Galaxy Tab launch Product Release Sony answers Product Release Chibi Chibi Burger other Jiexpo Kemayoran promoted TV Event Figure 6: Example future calendar entries extracted by our system for the week of November 7th. Data was collected up to November 5th. For each day, we list the top 5 events including the entity, event phrase, and event type. While there are several errors, the majority of calendar entries are informative, for example: the Muslim holiday eid-ul-azha, the release of several videogames: Modern Warfare 3 (MW3) and Skyrim, in addition to the release of the new playstation 3D display on Nov 13th, and the new iPhone 4S in Hong Kong on Nov 11th. # calendar entries 100 500 1,000 ngram baseline 0. 50 0. 6 0. 44 entity + date 0. 90 0. 66 0. 52 precision event phrase event 0. 86 0. 56 0. 42 type 0. 72 0. 54 0. 40 entity + date + event + type 0. 70 0. 42 0. 32 Table 5: Evaluation of precision at di? erent recall levels (generated by varying the threshold of the G2 statistic). We evaluate the top 100, 500 and 1,000 (entity, date) pairs. In addition we evaluate the precision of the most frequently extracted event phrase, and the predicted event type in association with these calendar entries. Also listed is the fraction of cases where all predictions (â€Å"entity + date + event + type†) are correct. We also compare against the precision of a simple ngram baseline which does not make use of our NLP tools. Note that the ngram baseline is only comparable to the entity+date precision (column 3) since it does not include event phrases or types. remains high enough to display to users (in a ranked list). In addition to being less likely to come from extraction errors, highly ranked entity/date pairs are more likely to relate to popular or important events, and are therefore of greater interest to users. In addition we present a sample of extracted future events on a calendar in ? ure 6 in order to give an example of how they might be presented to a user. We present the top 5 entities associated with each date, in addition to the most frequently extracted event phrase, and highest probability event type. 9. RELATED WORK While we are the ? rst to study open domain event extraction within Twitter, there are two key related strands of research: extracting speci? c types of events from Twi tter, and extracting open-domain events from news [43]. Recently there has been much interest in information extraction and event identi? cation within Twitter. Benson et al. 5] use distant supervision to train a relation extractor which identi? es artists and venues mentioned within tweets of users who list their location as New York City. Sakaki et al. [49] train a classi? er to recognize tweets reporting earthquakes in Japan; they demonstrate their system is capable of recognizing almost all earthquakes reported by the Japan Meteorological Agency. Additionally there is recent work on detecting events or tracking topics [29] in Twitter which does not extract structured representations, but has the advantage that it is not limited to a narrow domain. Petrovi? t al. investigate a streaming approach to identic fying Tweets which are the ? rst to report a breaking news story using Locally Sensitive Hash Functions [40]. Becker et al. [3], Popescu et al. [42, 41] and Lin et al. [28] inv estigate discovering clusters of related words or tweets which correspond to events in progress. In contrast to previous work on Twitter event identi? cation, our approach is independent of event type or domain and is thus more widely applicable. Additionally, our work focuses on extracting a calendar of events (including those occurring in the future), extract- . 4 Error Analysis We found 2 main causes for why entity/date pairs were uninformative for display on a calendar, which occur in roughly equal proportion: Segmentation Errors Some extracted â€Å"entities† or ngrams don’t correspond to named entities or are generally uninformative because they are mis-segmented. Examples include â€Å"RSVP†, â€Å"Breaking† and â€Å"Yikes†. Weak Association between Entity and Date In some cases, entities are properly segmented, but are uninformative because they are not strongly associated with a speci? c event on the associated date, or are involved in ma ny di? rent events which happen to occur on that day. Examples include locations such as â€Å"New York†, and frequently mentioned entities, such as â€Å"Twitter†. ing event-referring expressions and categorizing events into types. Also relevant is work on identifying events [23, 10, 6], and extracting timelines [30] from news articles. 8 Twitter status messages present both unique challenges and opportunities when compared with news articles. Twitter’s noisy text presents serious challenges for NLP tools. On the other hand, it contains a higher proportion of references to present and future dates. Tweets do not require complex reasoning about relations between events in order to place them on a timeline as is typically necessary in long texts containing narratives [51]. Additionally, unlike News, Tweets often discus mundane events which are not of general interest, so it is crucial to exploit redundancy of information to assess whether an event is signi? cant. Previous work on open-domain information extraction [2, 53, 16] has mostly focused on extracting relations (as opposed to events) from web corpora and has also extracted relations based on verbs. In contrast, this work extracts events, using tools adapted to Twitter’s noisy text, and extracts event phrases which are often adjectives or nouns, for example: Super Bowl Party on Feb 5th. Finally we note that there has recently been increasing interest in applying NLP techniques to short informal messages such as those found on Twitter. For example, recent work has explored Part of Speech tagging [19], geographical variation in language found on Twitter [13, 14], modeling informal conversations [44, 45, 9], and also applying NLP techniques to help crisis workers with the ? ood of information following natural disasters [35, 27, 36]. 1. ACKNOWLEDGEMENTS The authors would like to thank Luke Zettlemoyer and the anonymous reviewers for helpful feedback on a previous draft. This research was supported in part by NSF grant IIS-0803481 and ONR grant N00014-08-1-0431 and carried out at the University of Washington’s Turing Center. 12. REFERENCES [1] J. Allan, R. Papka, and V . Lavrenko. On-line new event detection and tracking. In SIGIR, 1998. [2] M. Banko, M. J. Cafarella, S. Soderl, M. Broadhead, and O. Etzioni. Open information extraction from the web. In In IJCAI, 2007. [3] H. Becker, M. Naaman, and L. Gravano. Beyond trending topics: Real-world event identi? ation on twitter. In ICWSM, 2011. [4] C. Bejan, M. 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Heilman, D. Yogatama, J. Flanigan, and N. A. Smith. Part-of-speech tagging 10. CONCLUSIONS We have presented a scalable and open-domain approach to extracting and categorizing events from status messages. We evaluated the quality of these events in a manual evaluation showing a clear improvement in performance over an ngram baseline We proposed a novel approach to categorizing events in an open-domain text genre with unknown types. Our approach based on latent variable models ? rst discovers event types which match the data, which are then used to classify aggregate events without any annotated examples. Because this approach is able to leverage large quantities of unlabeled data, it outperforms a supervised baseline by 14%. A possible avenue for future work is extraction of even richer event representations, while maintaining domain independence. 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The improvement in technology

Introduction The past decade has seen business trends receive a great upgrade due to the influx of technology. The improvement in technology has greatly affected the methods means and manner in which businesses choose to conduct their activities. Technology has been the greatest determinant of business growth for a variety of reasons.Advertising We will write a custom essay sample on The improvement in technology specifically for you for only $16.05 $11/page Learn More The better technology the industry has, the greater the computing power and in effect the faster, persuasive and competitive the product becomes. Technology facilitates an effective harness of talent, resources and ideas from the organisations structure (Boorsma Wolfgang 2007, p9). Today the influx of virtual business enabled by various technological business modules and vehicles has created a new approach to decision-making as well as business-to-business marketing. It would be difficult to ignore the prevalence of business modules such as Facebook which have flourished through social networking to secure a subscriber network of over 400 million people across the globe. Driven by a cost cutting objective technology continues to present new deployment methods which are aimed at reducing the cost of acquisition, maintenance as well upgrade of the technology adopted. This has made them a more attractive option as compared to alternative models and approaches to doing business. Cloud computing for example has opened a window of opportunities for majority if not all business players by offering new approaches to the concept of demand and supply. The consumer on his part is provided a variety of ways to derive utility from products, the entrepreneur also get an opportunity to expand their expansion ambitions to new markets breaching the geographical and structural limitations (Boorsma Wolfgang 2007, p9). Companies and businesses therefore have to make important decision s on how much investment to make in technology and in the transformation of the business models to harness new opportunities presented by new technology Markets operating a business-to-business model are characterised by a rather long and complicated buying process that is complicated further by the high costs of operation involved. It therefore follows that the model demands a fare share of objective and purposeful personalised communication. Traditionally the communication models used have been the face-to-face approach due to their convenience speed and immediate response ability.Advertising Looking for essay on other technology? Let's see if we can help you! Get your first paper with 15% OFF Learn More They have also been commonly used due to their flexibility in delivery of the message. The parties can customize the message to accommodate a change in circumstance as well as new circumstances. This is greatly attributed to the oligopolistic nature of these markets presenting a highly imbalanced seller to buyer ration. These aspects have been responsible for the general trend and direction of the business-to-business models. As De Pelsmacker et al (2004, p59) puts it the general trend has been to focus on personal selling alongside trade shows as the central marketing elements. Others suggest alternatives methods such as advertisements in business journals as the most appropriate methods of informing the consumer of the availability of a specific brand for their choosing and purchase. Despite the effectiveness of these methods however the emergence of new business marketing methods and options such as direct mail, online market strategies as well as database management have created a great indifference for managers and executives. They have to make investment decisions between expensive technologies that have a promise of high results and run the risk of obsolesce of the technology as opposed to sticking to the traditional methods of marketing and consumer outreach approaches. I will examine how the emerging technology and communication has affected the business-to-business buying process and decision-making. Argument A long-standing measure of a successful entrepreneur is their ability to organise groups of market participants to create a market. The influx of technology has created a reliable and viable method of doing just that through the internet in the context of internet marketing. The digital revolution has infected the marketing process with a wave of transformation that has progressively increased over the past few years. The digital influence on the various market and market players has fuelled an enthusiasm that is directed at the various digital options and choices in business models. This revolution has also been of great help to entrepreneurs and sellers who get an opportunity to centralise their efforts to embrace the consumer based business models. This therefore increases their level of consumer service by blending various digital options and elements. Digital marketing is however very different from internet marketing and is often but erroneously mistaken to mean the latter. Generally, internet marketing is a typical example of digital marketing since the tools of digital marketing include the internet alongside other related tools such as television channels, cell phones as well as wireless networks and connections.Advertising We will write a custom essay sample on The improvement in technology specifically for you for only $16.05 $11/page Learn More These tools if well employed have a great capacity to influence the buyer’s decision on whether to buy or not to buy or not. The buyer will be more convinced by a good presentation format that is technologically compliant with the recent trends that relate with them and express a futuristic impression. This however requires great monetary investment as well as strict and proper management to be a ble to achieve results. The technology for example must be compatible with the organisations goals objectives and strategy to avoid conflict and retrogressive or irrelevant technologies. As such, innovation in technology keeps presenting new opportunities and methods of engagement in the buying process and decision-making. This however comes at its own cost. From open source software developers to social network streamers such as Facebook and Twitter the market has switched digital. The open source websites boast of over 68 million bloggers who participate in product evaluation and in the distribution of product information. Customer relations have therefore been greatly enhanced through digital innovation. The players in the business-to-business market have an opportunity to instantly respond to each other’s questions fears and suggestions. A company therefore, lowers the cost of serving its customers by investing in an operational and suitable Web based customer service sol ution. This option allows the company to monitor its performance through the number of complains or complementary comments it receives through the customer service tool. Innovation in technology has gone an extra mile by offering a word of mouth Web based marketing option that allows buyers to share their experience with the specific product for others to see and hear. Sellers on the other hand get to explain verbatim the additional facilities offered by their product over and above their competitors (Immelt, Govindarajan Trimble 2009, p57). In the near future therefore the buy or sell decision will greatly rely on how good the technology conveys the information between the participants of such a market. Technology therefore has created an opportunity to tap into communities and create value from the formed groupings. This therefore implies that companies must comprehensively research before engaging with a potential service provider in relation to technology.Advertising Looking for essay on other technology? Let's see if we can help you! Get your first paper with 15% OFF Learn More Successful communication is a two way process with feed forward and feedback. Technology has also facilitated communication between the buyers and sellers by allowing the parties to supply feedback on the various concerns raised by the participants. This maintains a continuing participation and stimulates the level of commitment by the parties to the buying and selling decisions. As previously discussed, technology has allowed organisations to breach their limits in manpower, resource and geography through technological implements. Research suggests that this attribute of technological influence taps into a world of talent allowing companies to sustain flexibility and create volatility in business relations. Technology has rendered the market more porous allowing companies to work above the constraints of corporate infrastructure. In the past, this has been seen to work very well especially during the economic recession that left most companies with few workable option thereby causi ng companies to push for sustainable networks (Gawer 2010). Typically, the quality of talent an organisation can access in resolving technical client problems would be constrained by the company’s resources being structural and economic. An engineering company for instance,is only as good as its best engineer and therefore it can only be as good as the best salary it can offer to its engineers as the best ones come at a price. Technology has however made it easier for a manager to map knowledge sources with information hubs and a worldwide staff. This facilitates better utilisation of talent and increases the quality of unit innovation among its operation units. The various projects a manager undertakes are therefore authorised and assessed by the best of the best among experts in the specific specialty through the global network. This approach draws input from all calibres of employees ranging from fresh graduates to retirees. A good example of these labour markets is the Me chanical Turk courtesy of Amazon.com which specializes in selling expertise and consultancy as well as problem solving (Prahalad 2009). Despite this advantage and growth potential, management conservatism and bureaucracy still confines most companies to the talent and quality of its full time employees whose limits go only as far as the organisations’ structure. Technological advancement and innovation continue to offer new options every other day. In the near future, these options will be too many and the big question will be one of collaboration. It is important to ensure that any such engaged resource is exploited to its full potential. Essentially different innovations have different potential and capacities. The efficiency however depends on the collaboration of resources in the organisation. The collaboration leads to economies of scale and capacity. Teleconferencing and video conferencing for example has worked as a cost effective tool that saves on time and travel cos ts for the selling managers and business consultants. It also allows for more flexibility in the organisations capacity. The buyer’s decision to buy is therefore greatly influenced by convincing the sales executive in the video conference session. The buying process therefore still maintains an aspect of the interpersonal contact and dimension. In any buying process, the participants will always be concerned about history, authenticity and a promise of future consistency in service delivery. The transactions need to be authenticated to create assurance and confidence. The traditional approach would be for the participants to test, see or try the commodity before buying. Technology has facilitated automation of this process through the adoption of the radiofrequency identification and similar technologies. These create an information system that has assets in the form of elements of the system. One good such example is in the insurance industry where a company can keep account of the driver’s behaviour for the purpose of evaluation of their risk profile and for the purpose of payment of compensation should the risk materialize (Barabasi 2009). Technology has increased the accessories of the buying decision by allowing parties to offer guarantees of safety and an assurance of quality. More advanced innovation has enabled proactive action in luxury automobiles to engage intelligent action just before an accident occurs. In the medical industry the innovation has created an opportunity for cheaper more effective medical surveillance and protective mechanism against diseases and preventable illnesses. The process involves body implants that keep a record of body changes for the purpose of medical adjustments and medical prescription observation and supervision. The information collected allows for a more proper diagnosis of body problems. This not only guarantees the authenticity of products in the buying process but also guarantees safety. A good buy decision relies on the level of information relied on by the decision maker. This information would ordinarily be available only if gathered manually from the field or through trial and experimentation. These however are timely and expensive engagements that need not be undertaken thanks to technological innovation. Commonly referred to as the â€Å"big data,† the information system alternative offers access to smart assets for the buyer to choose from coupled with product information to facilitate their evaluation and information to ensure that the buyer’s expectations are adequately met. This allows the buyer to evaluate different product combinations at a lower cost as opposed to physical examination and testing or sampling. Technology has also allowed specialists, analysts and marketers to conduct purpose based trials and experiments on product combinations depending on customer expectations. The customers’ expectations are gathered from the social media we bsites and product review search engines. The experiment involves putting product combination for the discussion review and evaluation by the consumers (Thomke 2001, p66). Their responses through blogs and comments on these websites create a rating mechanism for these product combinations. These have also been used to adjust prices on a periodic basis to conform to the prevailing circumstances and the data provided by real-time data monitors on social media. From a corporate responsibility perspective, the buying process in certain circumstances caused environmental stress. This is partially due to the depletion of the existing resources and partially due to the waste generated by the process. Technology has facilitated a change in the level of responsibility of the participants of the business market by offering environmental friendly alternatives that go towards conservation and preservation of resources. The green data movement for instance, creates an opportunity to conserve ene rgy by developing environmental friendly implements that have automated energy saving mechanisms. Undeniably, the responsibility to preserve the environment falls on all and every stakeholder. Technology has therefore facilitated the principles of sustainability in the buying process by facilitating cost sharing and harmonised action (McAfee 2009). The mitigation mechanisms offered by technology also provide a quantity analysis. This information can be used in the monitoring supervision and reporting of the benefits as weighed against the damage contributed by information technology. Every company looks to reduce its fixed costs which account for the least possible price they can quote for the consumer. Business to business customers specifically invest in cost cutting alternatives and are more willing to maintain a cost as variable and terminable as opposed to a determinate fixed cost. Transport for instance, can be fixed or variable depending on the approach adopted. If a consumer acquires a bus they write it off as a fixed cost distributed evenly over the useful life of the product. In the alternative, technology has allowed for a re- evaluation of this product into a service where the consumer can acquire the purpose of the product as opposed to the physical product its self. The input of technology has allowed companies such as City Carshare to create a value added market for transportation services as an alternative to the purchase of transport equipment. The transportation service is easier to a count for and is more reliable and takes a corporate value approach. The cost then changes to a variable cost, which is adjusted on a periodic basis. It is also a more economical approach since the service is only paid for when it is rendered and it is paid for in the same measure of utility. This has changed the business-to-business concept through outsourcing which draws from the indefinite global resource. Transactions and business decisions gain value throug h interaction and exchange of information and communication. The traditional business model relies on the face-to-face interaction communication and information exchange. Technology has however transformed the business-to-business model to a multisided business model from a two-side model by allowing a three-way transaction. The advertising aspect in a newspaper allows newspapers to generate their revenue while still offering the users content. This creates a reliable market of defined sellers and many consumers in which case the consumers are segmented based on the side of the transaction and the benefit they expect to derive (Carr 2009). Relevance and suitability of a product are serious considerations in the buying decision. Therefore, the appropriateness of a service or product to a specific consumer environment and circumstance goes a long way in persuading the consumer to acquire or purchase the product. Technology has allowed the business-to-business communication process to adjust to the specific situations and circumstances through different user interfaces that adjust in language circumstance and conditions. The financial sector business to business model has greatly advanced in rural Africa through retail banking under the M-Pesa module that offers a connection between bank accounts and cell phones allowing up to 8 million to access banking services. The use of virtual cash services allows the users to access funds even in remote areas by visiting licensed shops. It is also a multisided method that allows companies to transfer funds to each other and to their employees and from employees to the companies and institutions such as banks (Bryan Joyce 2007). Conclusion The future of technology in business is bright as new methods of operation and interaction continue to emerge. The impact of technology on business transactions and decisions will also continue to gradually increase creating a dependent relationship in regard to decision making choice an d preference (Brynjolfsson Saunders 2009). Technology creates a capacity and opportunity for competitive advantage. The message is clear, organisations should acknowledge the role if innovation and technology in the business process as a strategy towards growth and competitive advantage (Malone 2004). References Barabasi A 2009, How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life, Plume, New York. Boorsma, B Wolfgang W 2007, ‘Connected urban development, Innovation for sustainability’, NATOA Journal, Volume 15, Number 4, pp.5–9. Bryan, L, Joyce C, 2007, Mobilizing Minds, Creating Wealth from Talent in the 21st-Century Organization, McGraw-Hill, New York. Brynjolfsson, E., Saunders, A 2009, Wired for Innovation, How Information Technology is Reshaping the Economy, The MIT Press, Cambridge. Carr, N 2009, The Big Switch, Rewiring the World, from Edison to Google, Norton Company, New York. De Pelsmacker, P., Geuens, M. Van den Bergh, J 2004, Marketing communications: a European perspective. Pearson Education. Essex. Gawer A 2010, Platforms, Markets and Innovation, Edward Elgar Publishing, Cheltenham. Immelt, R., Govindarajan, V Trimble, C 2009, ‘How GE is disrupting itself’, Harvard Business Review, Volume 87, Number 10, pp. 56–65. Malone, T 2004, The Future of Work, How the New Order of Business Will Shape Your Organization, Your Management Style, and Your Life, MA, Harvard Business Press, Cambridge. McAfee, A 2009, Enterprise 2.0, New Collaborative Tools for Your Organization’s Toughest Challenges, Harvard Business School Press, Cambridge. Prahalad, C 2009, The Fortune at the Bottom of the Pyramid, Eradicating Poverty Through Profits, Wharton School Publishing, Philadelphia. Thomke, S 2001, ‘Enlightened experimentation, The new imperative for innovation’, Harvard Business Review, Volume 79, Number 2, pp. 66–75. This essay on The improvement in technology was written and submitted by user Abb1ga1l to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.