Using Conditional Random Fields to Extract Contexts and Answers of Questions from Online Forums
Shilin Ding, Gao Cong, Chin-Yew Lin, Xiaoyan Zhu · 2008
Online forum discussions often contain vast amounts of questions that are the focuses of discussions. Extracting contexts and answers together with the questions will yield not only a coherent forum summary but also a valuable QA knowledge base. In this paper, we propose a general framework based on Conditional Random Fields (CRFs) to detect the contexts and answers of questions from forum threads. We improve the basic framework by Skip-chain CRFs and 2D CRFs to better accommodate the features of forums for better performance. Experimental results show that our techniques are very promising. 1