Query expansion for exploratory search with subtopic discovery in Community Question Answering

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Conference Proceeding
Proceedings of the International Joint Conference on Neural Networks, 2016, 2016-October pp. 4715 - 4720
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© 2016 IEEE. Exploratory search is cumbersome with today's search engines, where a user aims to better understand complex concepts. Query expansions techniques have been widely used in exploratory search. However, query expansions often recommend queries that differ from the user's search intentions due to different contexts. Yet, many of users' needs could be addressed by asking people via popular Community Question Answering (CQA) services. In this paper, we investigate query expansion techniques for exploratory search using the resources of CQA to discover the user's search intentions. Specifically, we denote the explicit intuition as the subtopic that supports the user's exploratory task. We propose the method CqaQuExp to mine the subtopics, which mainly contains three subtask: Question retrieval, where we extract the questions and corresponding answers from CQA; subtopic mining, where we discover the subtopics based on the extracted information; Candidate concepts discovery, where we select the candidate concepts from the discovered subtopics for query expansion. Experimental results on real-world data from Yahoo! Answers demonstrate the effectiveness of the proposed methods.
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