Paper: Answering Opinion Questions with Random Walks on Graphs

ACL ID P09-1083
Title Answering Opinion Questions with Random Walks on Graphs
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

Opinion Question Answering (Opinion QA), which aims to find the authors’ sen- timental opinions on a specific target, is more challenging than traditional fact- based question answering problems. To extract the opinion oriented answers, we need to consider both topic relevance and opinion sentiment issues. Current solu- tions to this problem are mostly ad-hoc combinations of question topic informa- tion and opinion information. In this pa- per, we propose an Opinion PageRank model and an Opinion HITS model to fully explore the information from different re- lations among questions and answers, an- swers and answers, and topics and opin- ions. By fully exploiting these relations, the experiment results show that our pro- posed algorithms outperform several state of the art baselines on be...