Mining Wikipedia and Yahoo! Answers for question expansion in Opinion QA
|Mining Wikipedia and Yahoo! Answers for question expansion in Opinion QA|
|Author(s)||Miao Y., Li C.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Opinion QA, Question expansion, Wikipedia, Yahoo! answers (Extra: Background information, Expansion methods, Opinion QA, Question Answering, Question expansion, Sentiment analysis, Wikipedia, Yahoo! answers, Data mining, Expansion)|
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|Web||Ask, Bing, Google (PDF), Yahoo!|
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Mining Wikipedia and Yahoo! Answers for question expansion in Opinion QA is a 2010 conference paper written in English by Miao Y., Li C. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
Opinion Question Answering (Opinion QA) is still a relatively new area in QA research. The achieved methods focus on combining sentiment analysis with the traditional Question Answering methods. Few attempts have been made to expand opinion questions with external background information. In this paper, we introduce the broad-mining and deep-mining strategies. Based on these two strategies, we propose four methods to exploit Wikipedia and Yahoo! Answers for enriching representation of questions in Opinion QA. The experimental results show that the proposed expansion methods perform effectively for improving existing Opinion QA models.
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