Thread Segmentation Based Answer Detection in Chinese Online Forums

Detecting answers in the threads is an essential task for the online forum oriented question-answer (QA) pair mining. In the forum threads, there normally exist implicit discussion structures with the valuable indicating information for the answer detecting models to locate the best answers. This paper proposes a thread segmentation based answer detecting approach: a forum thread is reorganized into several segments, and a group of features reflecting the discussion structures are extracted based on the segmentation results. Utilizing the segment information, a strategy is put forward to find the best answers. By evaluating the candidate answers in different types of segments with different models, the strategy filters the samples that mislead the decision. The experimental results show that our approach is promising for mining the QA resource in the online forums.