The Research On Answer Extraction Approach Of Web Based Automatic Question Answeing System

Compare to conventional Keywords-based search engine, Automatic Question Answering System (QA) can satisfy the users' retrieval command better, and it can give the answer that user need indeed, so it has the characteristics of convenience, celerity and high efficiency.Question classification is the first task of Question Answering System, and the precision of question classification has great effect on the subsequent processes. Answer extraction is the last and very important step in QA. The precision of a QA system will drop greatly if it can not give the correct answer in answer extraction module. After a deep investigation and research at question classification and answer extraction, the main work of the paper as follows:Firstly, in order to understand the questions' meaning better and get the information such as answer type, we propose a new Chinese question classification method—HowNet based Chinese question automatic classification, and then construct a question classification module with Maximum Entropy. The experiment results show that the correction percentage has obvious improvement than other similar experiment results.Secondly, after study the former work, in order to understand the sentences from semantic angle. We propose a new method that uses HowNet as knowledge database and combine with syntax analysis to extract answer. We experiment mainly at number questions and achieve a satisfactory result.Thirdly, answer validation can give necessary revision and feedback. After research the correlative study, we induce answer validation in the last phrase of QA.Finally, we test the method proposed in this paper by an integral QA and give the evaluation results.