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- W2066404111 abstract "Abstract We study personalized web-ranking algorithms based on the existence of document clusterings. Motivated by topic-sensitive page ranking [Haveliwala 03], we develop and implement an efficient “local-cluster” algorithm by extending the web search algorithm of [Achilioptas et al. 01]. We propose some formal criteria for evaluating such personalized ranking algorithms and provide some preliminary experiments in support of our analysis. Both theoretically and experimentally, our algorithm differs significantly from Topic-Sensitive PageRank." @default.
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- W2066404111 date "2009-01-01" @default.
- W2066404111 modified "2023-09-26" @default.
- W2066404111 title "Criteria for Cluster-Based Personalized Search" @default.
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- W2066404111 doi "https://doi.org/10.1080/15427951.2009.10390647" @default.
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