Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media
Community Question Answering has emerged as a popular and effective paradigm for a wide range of information needs. For example, to find out an obscure piece of trivia, it is now possible and even very effective to post a question on a popular community QA site such as Yahoo! Answers, and to rely on other users to provide answers, often within min-utes. The importance of such community QA sites is magni-fied as they create archives of millions of questions and hun-dreds of millions of answers, many of which are invaluable for the information needs of other searchers. However, to make this immense body of knowledge accessible, effective answer retrieval is required. In particular, as any user can contribute an answer to a question, the majority of the content refficts personal, often unsubstantiated opinions. A ranking that combines both relevance and quality is required to make such archives usable for factual information retrieval. This task is challenging, as the structure and the contents of community QA archives diffr significantly from the web setting. To address this problem we present a general ranking framework for factual information retrieval from social media. Results of a large scale evaluation demonstrate that our method is highly effective at retrieving well-formed, fac-tual answers to questions, as evaluated on a standard factoid QA benchmark. We also show that our learning framework can be tuned with the minimum of manual labeling. Finally, we provide result analysis to gain deeper understanding of which features are signiflant for social media search and re-trieval. Our system can be used as a crucial building block for combining results from a variety of social media content with general web search results, and to better integrate so-cial media content for effective information access.
Community Question Answering Ranking
Jiang Bian Yandong Liu Eugene Agichtein Hongyuan Zha
College of Computing Georgia Institute of Technology Atlanta, GA 30332 Math & Computer Science Department Emory University Atlanta, GA 30332
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）