Open domain event extraction from twitter
العنوان: | Open domain event extraction from twitter |
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المؤلفون: | Alan Ritter, null Mausam, Oren Etzioni, Sam Clark |
المصدر: | KDD |
بيانات النشر: | ACM, 2012. |
سنة النشر: | 2012 |
مصطلحات موضوعية: | Information extraction, Categorization, Computer science, business.industry, Event (computing), Aggregate (data warehouse), Open domain, Artificial intelligence, business, computer.software_genre, Machine learning, computer, Natural language processing |
الوصف: | Tweets are the most up-to-date and inclusive stream of in- formation 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 first open-domain event-extraction and categorization system for Twitter. We demonstrate that accurately extracting an open-domain calendar of significant 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.comTest; Our NLP tools are available at http://github.com/aritterTest/ twitter_nlp. |
الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_________::9c89a440742b3760414a63055602ac02Test https://doi.org/10.1145/2339530.2339704Test |
حقوق: | OPEN |
رقم الانضمام: | edsair.doi...........9c89a440742b3760414a63055602ac02 |
قاعدة البيانات: | OpenAIRE |