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.
REF , propose a general framework based on Conditional Random Fields (CRFs) to detect the contexts and answers of questions from forum threads.
Using Conditional Random Fields to Extract Contexts and Answers of Questions from Online Forums
Annual Meeting Of The Association For Computational Linguistics
Computer Science