Search (228 results, page 1 of 12)

  • × language_ss:"e"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.09
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
    Language
    e
    Source
    Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  2. Jarvelin, K.: ¬A deductive data model for thesaurus navigation and query expansion (1996) 0.06
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    Date
    2. 3.1997 17:29:07
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  3. Gauch, S.; Chong, M.K.: Automatic word similarity detection for TREC 4 query expansion (1996) 0.06
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    Language
    e
    Source
    The Fourth Text Retrieval Conference (TREC-4). Ed.: K. Harman
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  4. Lund, K.; Burgess, C.; Atchley, R.A.: Semantic and associative priming in high-dimensional semantic space (1995) 0.05
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    Language
    e
    Source
    Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society: July 22 - 25, 1995, University of Pittsburgh / ed. by Johanna D. Moore and Jill Fain Lehmann
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  5. Smeaton, A.F.; Kelledy, L.; O'Donnell, R.: TREC-4 experiments at Dublin City University : thresholding posting lists, query expansion with WordNet and POS tagging of Spanish (1996) 0.05
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    Language
    e
    Source
    The Fourth Text Retrieval Conference (TREC-4). Ed.: K. Harman
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  6. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.04
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    Language
    e
    Source
    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
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  7. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.04
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    Date
    30. 3.2001 13:32:22
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  8. Ross, J.: ¬A new way of information retrieval : 3-D indexing and concept mapping (2000) 0.04
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    Date
    25. 2.1997 10:29:16
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  9. Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-enhanced search interfaces (2002) 0.04
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    Date
    18. 5.2002 17:29:00
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  10. Shiri, A.A.; Revie, C.: ¬The effects of topic complexity and familiarity on cognitive and physical moves in a thesaurus-enhanced search environment (2003) 0.04
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    Language
    e
    Source
    Journal of information science. 29(2003) no.6, S.517-
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  11. 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) 0.04
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    Date
    18.10.2016 13:52:29
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  12. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.03
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    e
    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  13. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.03
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    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  14. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.03
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    e
    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  15. Stojanovic, N.: On the query refinement in the ontology-based searching for information (2005) 0.03
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    Date
    5. 4.1996 15:29:15
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  16. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.03
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    Date
    1. 2.2016 18:25:22
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  17. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.03
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    Date
    1. 2.2016 18:25:22
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  18. Mäkelä, E.; Hyvönen, E.; Saarela, S.; Vilfanen, K.: Application of ontology techniques to view-based semantic serach and browsing (2012) 0.03
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    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  19. Baofu, P.: ¬The future of information architecture : conceiving a better way to understand taxonomy, network, and intelligence (2008) 0.03
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    Abstract
    The Future of Information Architecture examines issues surrounding why information is processed, stored and applied in the way that it has, since time immemorial. Contrary to the conventional wisdom held by many scholars in human history, the recurrent debate on the explanation of the most basic categories of information (eg space, time causation, quality, quantity) has been misconstrued, to the effect that there exists some deeper categories and principles behind these categories of information - with enormous implications for our understanding of reality in general. To understand this, the book is organised in to four main parts: Part I begins with the vital question concerning the role of information within the context of the larger theoretical debate in the literature. Part II provides a critical examination of the nature of data taxonomy from the main perspectives of culture, society, nature and the mind. Part III constructively invesitgates the world of information network from the main perspectives of culture, society, nature and the mind. Part IV proposes six main theses in the authors synthetic theory of information architecture, namely, (a) the first thesis on the simpleness-complicatedness principle, (b) the second thesis on the exactness-vagueness principle (c) the third thesis on the slowness-quickness principle (d) the fourth thesis on the order-chaos principle, (e) the fifth thesis on the symmetry-asymmetry principle, and (f) the sixth thesis on the post-human stage.
    Classification
    BBV (FH K)
    GHBS
    BBV (FH K)
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  20. Morato, J.; Llorens, J.; Genova, G.; Moreiro, J.A.: Experiments in discourse analysis impact on information classification and retrieval algorithms (2003) 0.03
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    Abstract
    Researchers in indexing and retrieval systems have been advocating the inclusion of more contextual information to improve results. The proliferation of full-text databases and advances in computer storage capacity have made it possible to carry out text analysis by means of linguistic and extra-linguistic knowledge. Since the mid 80s, research has tended to pay more attention to context, giving discourse analysis a more central role. The research presented in this paper aims to check whether discourse variables have an impact on modern information retrieval and classification algorithms. In order to evaluate this hypothesis, a functional framework for information analysis in an automated environment has been proposed, where the n-grams (filtering) and the k-means and Chen's classification algorithms have been tested against sub-collections of documents based on the following discourse variables: "Genre", "Register", "Domain terminology", and "Document structure". The results obtained with the algorithms for the different sub-collections were compared to the MeSH information structure. These demonstrate that n-grams does not appear to have a clear dependence on discourse variables, though the k-means classification algorithm does, but only on domain terminology and document structure, and finally Chen's algorithm has a clear dependence on all of the discourse variables. This information could be used to design better classification algorithms, where discourse variables should be taken into account. Other minor conclusions drawn from these results are also presented.
    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval

Years

Types

  • a 201
  • el 23
  • m 16
  • r 6
  • p 2
  • s 2
  • x 1
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