Automatic Construction of Semantic Dictionary for Question Categorization
Tianyong Hao, Xingliang Ni, Xiaojun Quan, Wenyin Liu
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. Full Text
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