Paper: CoCQA: Co-Training over Questions and Answers with an Application to Predicting Question Subjectivity Orientation

ACL ID D08-1098
Title CoCQA: Co-Training over Questions and Answers with an Application to Predicting Question Subjectivity Orientation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008
Authors

An increasingly popular method for finding information online is via the Community Question Answering (CQA) portals such as Yahoo! An- swers, Naver, and Baidu Knows. Searching the CQA archives, and rank- ing, filtering, and evaluating the sub- mitted answers requires intelligent processing of the questions and an- swers posed by the users. One impor- tant task is automatically detecting the question’s subjectivity orientation: namely, whether a user is searching for subjective or objective information. Unfortunately, real user questions are often vague, ill-posed, poorly stated. Furthermore, there has been little la- beled training data available for real user questions. To address these prob- lems, we present CoCQA, a co-training system that exploits the association be- tw...