Explicit search result diversification through sub-queries

  • Authors:

  • Rodrygo L. T. Santos;Jie Peng;Craig Macdonald;Iadh Ounis

  • Affiliations:

  • Department of Computing Science, University of Glasgow, UK;Department of Computing Science, University of Glasgow, UK;Department of Computing Science, University of Glasgow, UK;Department of Computing Science, University of Glasgow, UK

  • Venue:
  • ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
  • Year:
  • 2010

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Abstract

Queries submitted to a retrieval system are often ambiguous. In such a situation, a sensible strategy is to diversify the ranking of results to be retrieved, in the hope that users will find at least one of these results to be relevant to their information need. In this paper, we introduce xQuAD, a novel framework for search result diversification that builds such a diversified ranking by explicitly accounting for the relationship between documents retrieved for the original query and the possible aspects underlying this query, in the form of sub-queries. We evaluate the effectiveness of xQuAD using a standard TREC collection. The results show that our framework markedly outperforms state-of-the-art diversification approaches under a simulated best-case scenario. Moreover, we show that its effectiveness can be further improved by estimating the relative importance of each identified sub-query. Finally, we show that our framework can still outperform the simulated best-case scenario of the state-of-the-art diversification approaches using sub-queries automatically derived from the baseline document ranking itself.