Paper: A Structural Support Vector Method for Extracting Contexts and Answers of Questions from Online Forums

ACL ID D09-1054
Title A Structural Support Vector Method for Extracting Contexts and Answers of Questions from Online Forums
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors
  • Wen-Yun Yang (Shanghai Jiaotong University, Shanghai China)
  • Yunbo Cao (Shanghai Jiaotong University, Shanghai China; Microsoft Research Asia, Beijing China)
  • Chin-Yew Lin (Microsoft Research Asia, Beijing China)

This paper addresses the issue of extract- ing contexts and answers of questions from post discussion of online forums. We propose a novel and unified model by customizing the structural Support Vector Machine method. Our customization has several attractive properties: (1) it gives a comprehensive graphical representation of thread discussion. (2) It designs special inference algorithms instead of general- purpose ones. (3) It can be readily ex- tended to different task preferences by varying loss functions. Experimental re- sults on a real data set show that our meth- ods are both promising and flexible.