Query subtopic mining for search result diversification

Web search queries are usually short, ambiguous, and contain multiple aspects or subtopics. Different users may have different search intents (or information needs) when submitting the same query. The task of identifying the subtopics underlying a query has received much attention in recent years. In this paper, we propose a method that exploits query reformulations provided by three major Web search engines (WSEs) as a means to uncover different query subtopics. In this regard, we estimate the importance of the subtopics by introducing multiple query-dependent and query-independent features, and rank the subtopics by balancing relevancy and novelty. Our experiment with the NTCIR-10 INTENT-2 English Subtopic Mining test collection shows that our method outperforms all participants' methods in NTCIR-10 INTENT-2 task in terms of D#-nDCG@10.

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