DisC diversity: result diversification based on dissimilarity and coverage

  • Authors:
  • Marina Drosou;Evaggelia Pitoura

  • Affiliations:
  • University of Ioannina, Greece;University of Ioannina, Greece

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2012

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Abstract

Recently, result diversification has attracted a lot of attention as a means to improve the quality of results retrieved by user queries. In this paper, we propose a new, intuitive definition of diversity called DisC diversity. A DisC diverse subset of a query result contains objects such that each object in the result is represented by a similar object in the diverse subset and the objects in the diverse subset are dissimilar to each other. We show that locating a minimum DisC diverse subset is an NP-hard problem and provide heuristics for its approximation. We also propose adapting DisC diverse subsets to a different degree of diversification. We call this operation zooming. We present efficient implementations of our algorithms based on the M-tree, a spatial index structure, and experimentally evaluate their performance.