Search (49 results, page 2 of 3)

  • × language_ss:"e"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995) 0.00 
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    Date
    29. 1.1996 18:42:14
  2. Greenberg, J.: Optimal query expansion (QE) processing methods with semantically encoded structured thesaurus terminology (2001) 0.00 
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    29. 9.2001 14:00:11
  3. Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-assisted search term selection and query expansion : a review of user-centred studies (2002) 0.00 
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    Source
    Knowledge organization. 29(2002) no.1, S.1-19
  4. Khan, M.S.; Khor, S.: Enhanced Web document retrieval using automatic query expansion (2004) 0.00 
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    Journal of the American Society for Information Science and technology. 55(2004) no.1, S.29-40
  5. Shiri, A.A.; Revie, C.: End-user interaction with thesauri : an evaluation of cognitive overlap in search term selection (2004) 0.00 
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    Date
    29. 8.2004 16:27:16
  6. Menczer, F.: Lexical and semantic clustering by Web links (2004) 0.00 
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    Date
    9. 1.2005 19:20:29
  7. Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005) 0.00 
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    Source
    The Semantic Web: research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings. Eds.: A. Gómez-Pérez u. J. Euzenat
  8. Vechtomova, O.; Robertson, S.E.: ¬A domain-independent approach to finding related entities (2012) 0.00 
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    Date
    27. 1.2016 18:44:29
  9. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.00 
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    Date
    16.11.2008 16:22:48
  10. Zeng, M.L.; Gracy, K.F.; Zumer, M.: Using a semantic analysis tool to generate subject access points : a study using Panofsky's theory and two research samples (2014) 0.00 
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  11. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.00 
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    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
  12. Greenberg, J.: Automatic query expansion via lexical-semantic relationships (2001) 0.00 
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    Date
    29. 9.2001 13:59:48
  13. Tudhope, D.; Blocks, D.; Cunliffe, D.; Binding, C.: Query expansion via conceptual distance in thesaurus indexed collections (2006) 0.00 
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    Date
    30. 7.2011 16:07:29
  14. Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008) 0.00 
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    9.11.2008 13:07:29
  15. Bando, L.L.; Scholer, F.; Turpin, A.: Query-biased summary generation assisted by query expansion : temporality (2015) 0.00 
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    Abstract
    Query-biased summaries help users to identify which items returned by a search system should be read in full. In this article, we study the generation of query-biased summaries as a sentence ranking approach, and methods to evaluate their effectiveness. Using sentence-level relevance assessments from the TREC Novelty track, we gauge the benefits of query expansion to minimize the vocabulary mismatch problem between informational requests and sentence ranking methods. Our results from an intrinsic evaluation show that query expansion significantly improves the selection of short relevant sentences (5-13 words) between 7% and 11%. However, query expansion does not lead to improvements for sentences of medium (14-20 words) and long (21-29 words) lengths. In a separate crowdsourcing study, we analyze whether a summary composed of sentences ranked using query expansion was preferred over summaries not assisted by query expansion, rather than assessing sentences individually. We found that participants chose summaries aided by query expansion around 60% of the time over summaries using an unexpanded query. We conclude that query expansion techniques can benefit the selection of sentences for the construction of query-biased summaries at the summary level rather than at the sentence ranking level.
  16. Gnoli, C.; Santis, R. de; Pusterla, L.: Commerce, see also Rhetoric : cross-discipline relationships as authority data for enhanced retrieval (2015) 0.00 
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    Source
    Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro
  17. Jiang, Y.; Bai, W.; Zhang, X.; Hu, J.: Wikipedia-based information content and semantic similarity computation (2017) 0.00 
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    Date
    23. 1.2017 14:06:29
  18. Athukorala, K.; Glowacka, D.; Jacucci, G.; Oulasvirta, A.; Vreeken, J.: Is exploratory search different? : a comparison of information search behavior for exploratory and lookup tasks (2016) 0.00 
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    Date
    18.10.2016 13:52:29
  19. Adhikari, A.; Dutta, B.; Dutta, A.; Mondal, D.; Singh, S.: ¬An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology (2018) 0.00 
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    Date
    29. 7.2018 11:40:33
  20. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.00 
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    Date
    22. 2.1996 13:14:10

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