Improving Question Retrieval in cQA Services Using a Dependency Parser

Kyoungman BAE  Youngjoong KO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.4   pp.807-810
Publication Date: 2017/04/01
Online ISSN: 1745-1361
Type of Manuscript: Special Section LETTER (Special Section on Data Engineering and Information Management)
Category: 
Keyword: 
question retrieval,  cQA service,  dependency,  language model,  

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Summary: 
The translation based language model (TRLM) is state-of-the-art method to solve the lexical gap problem of the question retrieval in the community-based question answering (cQA). Some researchers tried to find methods for solving the lexical gap and improving the TRLM. In this paper, we propose a new dependency based model (DM) for the question retrieval. We explore how to utilize the results of a dependency parser for cQA. Dependency bigrams are extracted from the dependency parser and the language model is transformed using the dependency bigrams as bigram features. As a result, we obtain the significant improved performances when TRLM and DM approaches are effectively combined.