Automatic Construction of Semantic Dictionary for Question Categorization

An automatic method for building a semantic dictionary from existing questions in a pattern-based question answering system is proposed for question categorization. This dictionary consists of two main parts: Semantic Domain Terms (SDT), which is a domain specific term list, and Semantic Labeled Terms (SLT), which contain common terms tagged with semantic labels. The semantic dictionary is built using the proposed method on a set of 2509 questions with semantic patterns in our system. 3390 questions without semantic patterns are used as ground truth to test its performance. Experimental results show that the precision of question classification is improved by 7.5% in average after using the constructed semantic dictionary compared with the baseline method.