Creator: Chen, Jiangping; Ge, He; Wu, Yan & Jiang, Shikun
Description: This paper discusses Question Answering (QA) combining multiple evidences. QA aims at identifying answers to users' natural language questions. A QA system can release the users from digesting large amounts of text in order to locate particular facts or numbers. The research has drawn great attention from several disciplines such as information retrieval, information extraction, natural language processing, and artificial intelligence. TREC QA track has provided comparable QA system evaluation on a set of test questions since 1999. The degree of difficulty of the test questions has increased substantially in recent two years, which push the research toward applying more sophisticated strategies and better understanding of English texts. This article discusses this research.
Contributing Partner: UNT College of Information