This paper addresses the issue of extracting 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 generalpurpose ones. (3) It can be readily extended to different task preferences by varying loss functions. Experimental results on a real data set show that our methods are both promising and flexible.
Extracting contexts and answers of questions from the online travel forum "TripAdvisor" by using a structural support vector machine (SVM) was conducted REF .
A Structural Support Vector Method for Extracting Contexts and Answers of Questions from Online Forums
EMNLP
Computer Science