Document (#36356)

Author

He, J.
Meij, E.
Rijke, M. de

Title

Result diversification based on query-specific cluster ranking

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.3, S.550-571

Year

2011

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.

Theme

Retrievalalgorithmen

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5. Tho, Q.T.; Hui, S.C.; Fong, A.C.M.: ¬A citation-based document retrieval system for finding research expertise (2007) 0.19

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