Zheng, ZhichengTang, YangLong, ChongBu, FanZhu, Xiaoyan2012-05-222012-05-222010-05Zheng, Z., Tang, Y., Long, C., Bu, F., & Zhu, X. (2010). Question Answering System Based on Community QA. Proceedings of the LREC 2010 Workshop on Web Logs and Question Answering (WLQA2010),Malta.http://hdl.handle.net/10625/49056LREC 2010 Workshop on Web Logs and Question Answering (WLQA2010)After a long period of research in factoid QA, such kind of questions has already been solved quite well. However, real users always concern on some more complicated questions such as ”Why XXXX?” or ”How XXXX?”. These questions are difficult to retrieve answers directly from internet, but the community question answering services provide good resources to solve these questions. As cQA portals like Yahoo! Answers and Baidu Zhidao have attracted over hundreds of millions of questions, these questions can be treated as users’ query log, and can help the QA systems understand the user’s questions better. Common approaches focus on using information retrieval techniques in order to provide a ranked list of questions based on their similarity to the query. Due to the high variance of quality of questions and answers, users have to spend lots of time on finding the truly best answers from retrieved results. In this paper, we develop an answer retrieval and summarization system which directly provides an accurate and comprehensive answer summary besides a list of similar questions to user’s query. To fully explore the information of questions and answers posted in the cQA, we adopt different strategies according to different situations. By this way, the system could output great answers to users’ questions in practice.Text1 digital file (p. 23-27 : ill.)enQUESTION ANSWER SYSTEMSINFORMATION RETRIEVALConference Paper