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Na, S.-H.; Kang, I.-S.; Roh, J.-E.; Lee, J.-H.: ¬An empirical study of query expansion and cluster-based retrieval in language modeling approach (2007)
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- Information processing and management. 43(2007) no.2, S.302-314
- Year
- 2007
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Abdelali, A.; Cowie, J.; Soliman, H.S.: Improving query precision using semantic expansion (2007)
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- Information processing and management. 43(2007) no.3, S.705-716
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- 2007
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Bhogal, J.; Macfarlane, A.; Smith, P.: ¬A review of ontology based query expansion (2007)
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- Information processing and management. 43(2007) no.4, S.866-886
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- 2007
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Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986)
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- Information processing and management. 22(1986) no.6, S.465-476
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Yang, L.; Ji, D.; Leong, M.: Document reranking by term distribution and maximal marginal relevance for chinese information retrieval (2007)
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- Information processing and management. 43(2007) no.2, S.315-326
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- 2007
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Sakai, T.: On the reliability of information retrieval metrics based on graded relevance (2007)
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- Information processing and management. 43(2007) no.2, S.531-548
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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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- 30. 3.2001 13:32:22
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Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000)
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- 25. 8.2005 17:42:22
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Dannenberg, R.B.; Birmingham, W.P.; Pardo, B.; Hu, N.; Meek, C.; Tzanetakis, G.: ¬A comparative evaluation of search techniques for query-by-humming using the MUSART testbed (2007)
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- Journal of the American Society for Information Science and Technology. 58(2007) no.5, S.687-701
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- 2007
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Chen, Z.; Fu, B.: On the complexity of Rocchio's similarity-based relevance feedback algorithm (2007)
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- Journal of the American Society for Information Science and Technology. 58(2007) no.10, S.1392-1400
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- 2007
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MacFarlane, A.; McCann, J.A.; Robertson, S.E.: Parallel methods for the update of partitioned inverted files (2007)
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- Aslib proceedings. 59(2007) no.4/5, S.367-396
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- 2007
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Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986)
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- 14. 6.2015 22:12:44
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Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986)
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- 14. 6.2015 22:12:56
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Urbain, J.; Goharian, N.; Frieder, O.: Probabilistic passage models for semantic search of genomics literature (2008)
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- Abstract
- We explore unsupervised learning techniques for extracting semantic information about biomedical concepts and topics, and introduce a passage retrieval model for using these semantics in context to improve genomics literature search. Our contributions include a new passage retrieval model based on an undirected graphical model (Markov Random Fields), and new methods for modeling passage-concepts, document-topics, and passage-terms as potential functions within the model. Each potential function includes distributional evidence to disambiguate topics, concepts, and terms in context. The joint distribution across potential functions in the graph represents the probability of a passage being relevant to a biologist's information need. Relevance ranking within each potential function simplifies normalization across potential functions and eliminates the need for tuning of passage retrieval model parameters. Our dimensional indexing model facilitates efficient aggregation of topic, concept, and term distributions. The proposed passage-retrieval model improves search results in the presence of varying levels of semantic evidence, outperforming models of query terms, concepts, or document topics alone. Our results exceed the state-of-the-art for automatic document retrieval by 14.46% (0.3554 vs. 0.3105) and passage retrieval by 15.57% (0.1128 vs. 0.0976) as assessed by the TREC 2007 Genomics Track, and automatic document retrieval by 18.56% (0.3424 vs. 0.2888) as assessed by the TREC 2005 Genomics Track. Automatic document retrieval results for TREC 2007 and TREC 2005 are statistically significant at the 95% confidence level (p = .0359 and .0253, respectively). Passage retrieval is significant at the 90% confidence level (p = 0.0893).
-
White, R.W.; Marchionini, G.: Examining the effectiveness of real-time query expansion (2007)
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- Information processing and management. 43(2007) no.3, S.685-704
- Year
- 2007
-
Jacso, P.: Testing the calculation of a realistic h-index in Google Scholar, Scopus, and Web of Science for F. W. Lancaster (2008)
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- Abstract
- This paper focuses on the practical limitations in the content and software of the databases that are used to calculate the h-index for assessing the publishing productivity and impact of researchers. To celebrate F. W. Lancaster's biological age of seventy-five, and "scientific age" of forty-five, this paper discusses the related features of Google Scholar, Scopus, and Web of Science (WoS), and demonstrates in the latter how a much more realistic and fair h-index can be computed for F. W. Lancaster than the one produced automatically. Browsing and searching the cited reference index of the 1945-2007 edition of WoS, which in my estimate has over a hundred million "orphan references" that have no counterpart master records to be attached to, and "stray references" that cite papers which do have master records but cannot be identified by the matching algorithm because of errors of omission and commission in the references of the citing works, can bring up hundreds of additional cited references given to works of an accomplished author but are ignored in the automatic process of calculating the h-index. The partially manual process doubled the h-index value for F. W. Lancaster from 13 to 26, which is a much more realistic value for an information scientist and professor of his stature.
-
MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004)
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- 20. 1.2007 18:30:22
-
Faloutsos, C.: Signature files (1992)
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- Date
- 7. 5.1999 15:22:48
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Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003)
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- 22. 3.2003 19:27:23
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Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
