KDEIM at NTCIR-12 IMine-2 Search Intent Mining Task: Query Understanding through Diversified Ranking of Subtopics

In this paper, we describe our participation in the Query Understanding subtask of the NTCIR-12 IMINE Task. We propose a method that extracts subtopics by leveraging the query suggestions from search engines. The importance of the subtopics with the query is estimated by exploiting multiple query-dependent and query-independent features with supervised feature selection. To diversify the subtopics, we employ maximummarginal relevance (MMR) framework based diversification technique by balancing the relevance and novelty. The best performance of our method achieves an I-rec of 0.7557, a D-nDCG of 0.6644, a D#-nDCG of 0.7100, and a QU-score of 0.5057 at the cutoff rank 10 for query understanding task.

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