Chinese question classification in community question answering

Community Question Answering (CQA) has become a popular and effective mean for seeking information on the Web. It is now possible and effective to post a question asked in natural language on a popular community Question Answering (QA) portal, and to rely on other users to provide answers. These online collaborative services are attracting users and questions at an explosive rate, while how to correctly categorize a given question is the first problem that a community QA system must dispose. Question classification plays a crucial important role in the community QA System because categorizing a given question correctly is beneficial to obtain accurate answers quickly. In this paper, we present a classifier based on the Support Vector Machine (SVM) machine learning algorithm, and develop a variety of lexical and semantic features for this task. Our experimental results, obtained from a large scale evaluation over thousands of real questions, show the feasibility and effectiveness of our approach.