Query Snowball: A Co-occurrence-based Approach to Multi-document Summarization for Question Answering

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概要

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• We propose a new method for query-oriented extractive multi-document summarization. To enrich the information need representation of a given query, we build a co-occurrence graph to obtain words that augment the original query terms. We then formulate the summarization problem as a Maximum Coverage Problem with Knapsack Constraints based on word pairs rather than single words. Our experiments with the NTCIR ACLIA question answering test collections show that our method achieves a pyramid F3-score of up to 0.313, a 36% improvement over a baseline using Maximal Marginal Relevance.

著者

• Okumura Manabu

  Precision And Intelligence Laboratory Tokyo Institute Of Technology

• SAKAI TETSUYA

  Microsoft Research Asia

• Morita Hajime

  Tokyo Institute of Technology

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