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Inside Siri's brain: The challenges of extending Apple's virtual assistant Macworld (blog) Similarly, both OS X and iOS have recently acquired several programming interfaces that can be used to analyze the syntax of a text document, although they...
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A great article about the difiiculties of basic sentiment analysis. The addition of linguistic analysis is helpful, but the problems of linguistic analysis, such as pronoun resolution and sentence-level disambiguation, are ones we can still improve upon.
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A good primer on the importance of data quality and how data quality can lead to better decisions. Within text analysis, the best implementations are ones where not only are the entities extracted, but ones where you can clean up the extraction and standardize it and create truly informative databases.
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Little Data is only little when compared to Big Data. It involves looking at just a slice of a larger data group. Erica Driver talks more about it's importance in a look back at the recent Text Analytics Summit in Boston.
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1. Be Clear: Is Your Problem Really A Big Data Problem? There are many big data problems out there requiring huge compute scale, innovations in computation paradigms, vast storage space and so on. But just because ...
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If you've ever wondered what big data means at an individual level, this realization about sums it up: "I could either keep dying my hair or retire a year earlier." It's those types of realizations Intuit hopes its heavy big data use will...
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In our latest white paper, Actionable Social Analytics: From Social Media Metrics to Business Insights we unveiled the Social Analytics Framework for Marketing and Sales Effectiveness.
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“Typically the entity extraction and content analysis components that we have developed really are designed to enable enterprises to be able to identify relationships between documents [and] begin to, for instance, generate ...
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Our vision is DeepMR, enabled by an ensemble of text analytics, sentiment analysis, behavioral analyses, and psychometric technologies — applied to social and online sources, as well as to traditional surveys — with the ...
Twitter was founded in 2006. Over the course of the last four years, in particular, we've seen a gigantic uptake of the platform by journalists, business leaders, brands, and celebrities. Due to the uptake of over 100 million active users on Twitter today and the fact that people are watching events together on the platform (elections, the Oscars, sports events) and making commentary, Francois Bar, Associate Professor of Communication at the University of Southern California and his team of researchers have explored sentiment analysis. The majority of Bar’s research is grounded in exploring social and economic impacts of information technologies. The interaction of millions of individuals through social networks generates vast amounts of data. With that data, teams from the Innovation Lab and at the Viterbi School of Engineering at USC are trying to analyze collective knowledge. Watch The video about sentiment analysis: http://www.forbes.com/sites/lorikozlowski/2012/04/24/twitter-and-our-feelings-real-time-sentiment-analysis/
Via Antonino Militello
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Big Data: $16.9 Billion opportunity for IT Services and Consulting Industry... ...
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The Office of the Director of National Intelligence (ODNI) is building a computer system capable of automatically analyzing the massive quantities of data gathered across the entire intelligence community and extracting information on specific...
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Gnip is dozens of social media APIs in one. Easy setup within 5 minutes. Millions of daily results from Twitter, Facebook, YouTube & more in Activity Streams & original formats. (RT @gnip: Looking to do text analytics on social media?
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Social Media is a tactic - a tool. If you have a great advertising campaign wherever it is, on TV and Social Media, just on TV, just on Social Media, whatever… then someone is probably likely to mention it on Twitter or blogs no ...
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This article deas with the new Twitter Certified Products Program. Iknow has experience with Attensity Analyze and Attensity 360, but more importantly can see that this is necessary for the future of Social Media Analysis to grow on all social media channels.
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The debate between Enterprise Search and Text Analysis should be over before it begins. In knowledge management, the best approaches combine both breadth, from Enterprise Search, and depth, from Text Analysis. Krish Krishnan goes deeper into this topic.
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Sentiment analysis of tutorial videos with a focus on how people create conversations in comments sections.
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This article provides tips for adding richer metadata and descriptors to content stored in SharePoint to make searching for content more precise
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Wonderful news!(Data Quality, What Matters to Analytics-Given ability to improve data requires analysis of data itself @textanalyticsfr http://t.co/t5NEieEb...)...
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The Institute for Statistics Education has several courses specifically devoted to text analytics taught by Dr. Nitin Indurkhya.
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The same article also says: ”BI uses both structured and unstructured data, but the former is easy to search, and the latter contains a large quantity of the information needed for analysis and decision making.
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“Sentiment is the poetry of the imagination”. Google has now started using Sentiment Analysis to rank websites on its search engine. This would slightly affect the rankings of all the existing ...
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Few have attempted to integrate these distinct disciplines -- but more should. ...
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While keyword analysis and entity extraction have been with us for a while, and are available from several data vendors, the availability of social media sources is relatively new, and has certainly captured the attention of many people looking ...
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I have been researching visualization of sentiment analysis and this web app has a pretty cool design.