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Recently, result diversification has attracted a lot of attention as a meansto improve the quality of results retrieved by user queries. In this paper, wepropose a new, intuitive definition of diversity called DisC diversity. A DisCdiverse subset of a query result contains objects such that each object in theresult is represented by a similar object in the diverse subset and the objectsin the diverse subset are dissimilar to each other. We show that locating aminimum DisC diverse subset is an NP-hard problem and provide heuristics forits approximation. We also propose adapting DisC diverse subsets to a differentdegree of diversification. We call this operation zooming. We present efficientimplementations of our algorithms based on the M-tree, a spatial indexstructure, and experimentally evaluate their performance.

DisC Diversity: Result Diversification based on Dissimilarity and Coverage