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• W2092552912 abstract "The ad hoc retrieval task is to find documents in a corpus that are relevant to a query. Inspired by the PageRank and HITS (hubs and authorities) algorithms for Web search, we propose a structural reranking approach to ad-hoc retrieval that applies to settings with no hyperlink information. We reorder the documents in an initially retrieved set by exploiting implicit asymmetric relationships among them. We consider generation links , which indicate that the language model induced from one document assigns high probability to the text of another. We study a number of reranking criteria based on measures of centrality in the graphs formed by generation links, and show that integrating centrality into standard language-model-based retrieval is quite effective at improving precision at top ranks; the best resultant performance is comparable, and often superior, to that of a state-of-the-art pseudo-feedback-based retrieval approach. In addition, we demonstrate the merits of our language-model-based method for inducing interdocument links by comparing it to previously suggested notions of interdocument similarities (e.g., cosines within the vector-space model).We also show that ourmethods for inducing centrality are substantially more effective than approaches based on document-specific characteristics, several of which are novel to this study." @default.
• W2092552912 created "2016-06-24" @default.
• W2092552912 creator A5041210904 @default.
• W2092552912 creator A5076876084 @default.
• W2092552912 date "2010-11-01" @default.
• W2092552912 modified "2023-10-16" @default.
• W2092552912 title "PageRank without hyperlinks" @default.
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• W2092552912 doi "https://doi.org/10.1145/1852102.1852104" @default.
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