Extracting Chinese Question-Answer Pairs from Online Forums

Baoxun Wang, Bingquan Liu, Chengjie Sun, Xiaolong Wang, Lin Sun

Abstract: Extracting question-answer pairs from online forums is a meaningful work due to the huge amount of valuable user generated resource contained in forums. In this paper we consider the problem of extracting Chinese question-answer pairs for the first time. We present a strategy to detect Chinese questions and their answers. We propose a sequential rule based method to find questions in a forum thread, then we adopt non-textual features based on forum structure to improve the performance of answer detecting in the same thread. Experimental results show that our techniques are very effective.