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Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006)
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- 2006
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Stock, W.G.: On relevance distributions (2006)
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Vechtomova, O.; Karamuftuoglu, M.: Elicitation and use of relevance feedback information (2006)
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Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986)
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White, K.J.; Sutcliffe, R.F.E.: Applying incremental tree induction to retrieval : from manuals and medical texts (2006)
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Lin, J.; Katz, B.: Building a reusable test collection for question answering (2006)
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Käki, M.: fKWIC: frequency-based Keyword-in-Context Index for filtering Web search results (2006)
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Bodoff, D.; Wong, S.P.-S.: Documents and queries as random variables : history and implications (2006)
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White, R.W.; Jose, J.M.; Ruthven, I.: ¬An implicit feedback approach for interactive information retrieval (2006)
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Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983)
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Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000)
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Shah, B.; Raghavan, V.; Dhatric, P.; Zhao, X.: ¬A cluster-based approach for efficient content-based image retrieval using a similarity-preserving space transformation method (2006)
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- 2006
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Cheng, C.-S.; Chung, C.-P.; Shann, J.J.-J.: Fast query evaluation through document identifier assignment for inverted file-based information retrieval systems (2006)
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Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986)
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Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986)
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Wills, R.S.: Google's PageRank : the math behind the search engine (2006)
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- Mathematical intelligencer. 28(2006) no.4, S.6-11
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- 2006
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Bar-Ilan, J.; Levene, M.; Mat-Hassan, M.: Methods for evaluating dynamic changes in search engine rankings : a case study (2006)
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- Journal of documentation. 62(2006) no.6, S.708-729
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- 2006
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Zhao, L.; Wu, L.; Huang, X.: Using query expansion in graph-based approach for query-focused multi-document summarization (2009)
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- Abstract
- This paper presents a novel query expansion method, which is combined in the graph-based algorithm for query-focused multi-document summarization, so as to resolve the problem of information limit in the original query. Our approach makes use of both the sentence-to-sentence relations and the sentence-to-word relations to select the query biased informative words from the document set and use them as query expansions to improve the sentence ranking result. Compared to previous query expansion approaches, our approach can capture more relevant information with less noise. We performed experiments on the data of document understanding conference (DUC) 2005 and DUC 2006, and the evaluation results show that the proposed query expansion method can significantly improve the system performance and make our system comparable to the state-of-the-art systems.
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MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004)
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- 20. 1.2007 18:30:22
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Faloutsos, C.: Signature files (1992)
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- Date
- 7. 5.1999 15:22:48
