Result diversification based on query‐specific cluster ranking

Jiyin He, Edgar Meij and Maarten de Rijke

Journal of the American Society for Information Science and Technology, 2011, vol. 62, issue 3, 550-571

Abstract: Result diversification is a retrieval strategy for dealing with ambiguous or multi‐faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query‐specific clustering and cluster ranking, in which diversification is restricted to documents belonging to clusters that potentially contain a high percentage of relevant documents. Empirical results show that the proposed framework improves the performance of several existing diversification methods. The framework also gives rise to a simple yet effective cluster‐based approach to result diversification that selects documents from different clusters to be included in a ranked list in a round robin fashion. We describe a set of experiments aimed at thoroughly analyzing the behavior of the two main components of the proposed diversification framework, ranking and selecting clusters for diversification. Both components have a crucial impact on the overall performance of our framework, but ranking clusters plays a more important role than selecting clusters. We also examine properties that clusters should have in order for our diversification framework to be effective. Most relevant documents should be contained in a small number of high‐quality clusters, while there should be no dominantly large clusters. Also, documents from these high‐quality clusters should have a diverse content. These properties are strongly correlated with the overall performance of the proposed diversification framework.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jamist:v:62:y:2011:i:3:p:550-571

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