Search (27 results, page 1 of 2)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × year_i:[2000 TO 2010}
  1. Ross, J.: ¬A new way of information retrieval : 3-D indexing and concept mapping (2000) 0.02
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  2. Gao, J.; Zhang, J.: Clustered SVD strategies in latent semantic indexing (2005) 0.01
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  3. Morato, J.; Llorens, J.; Genova, G.; Moreiro, J.A.: Experiments in discourse analysis impact on information classification and retrieval algorithms (2003) 0.01
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  4. Bai, J.; Nie, J.-Y.: Adapting information retrieval to query contexts (2008) 0.01
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  5. Bhogal, J.; Macfarlane, A.; Smith, P.: ¬A review of ontology based query expansion (2007) 0.01
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  6. Greenberg, J.: Optimal query expansion (QE) processing methods with semantically encoded structured thesaurus terminology (2001) 0.01
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  7. Nie, J.-Y.: Query expansion and query translation as logical inference (2003) 0.01
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  8. Küssow, J.: ALEPH 500 mit multilingualem Thesaurus (2003) 0.01
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  9. Lin, J.; DiCuccio, M.; Grigoryan, V.; Wilbur, W.J.: Navigating information spaces : a case study of related article search in PubMed (2008) 0.01
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  10. Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005) 0.01
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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
  11. Yan, X.; Li, X.; Song, D.: ¬A correlation analysis on LSA and HAL semantic space models (2004) 0.01
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    Source
    Computational and information science. First International Symposium, CIS 2004, Shanghai, China, December 16-18, 2004. Proceedings. Eds.: J. Zhang et al
  12. Greenberg, J.: Automatic query expansion via lexical-semantic relationships (2001) 0.01
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  13. Quiroga, L.M.; Mostafa, J.: ¬An experiment in building profiles in information filtering : the role of context of user relevance feedback (2002) 0.01
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  14. Niemi, T.; Jämsen, J.: ¬A query language for discovering semantic associations, part II : sample queries and query evaluation (2007) 0.01
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  15. Niemi, T.; Jämsen , J.: ¬A query language for discovering semantic associations, part I : approach and formal definition of query primitives (2007) 0.01
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  16. Bilal, D.; Kirby, J.: Differences and similarities in information seeking : children and adults as Web users (2002) 0.01
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  17. Tudhope, D.; Binding, C.; Blocks, D.; Cunliffe, D.: FACET: thesaurus retrieval with semantic term expansion (2002) 0.01
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    Abstract
    There are many advantages for Digital Libraries in indexing with classifications or thesauri, but some current disincentive in the lack of flexible retrieval tools that deal with compound descriptors. This demonstration of a research prototype illustrates a matching function for compound descriptors, or multi-concept subject headings, that does not rely on exact matching but incorporates term expansion via thesaurus semantic relationships to produce ranked results that take account of missing and partially matching terms. The matching function is based on a measure of semantic closeness between terms.The work is part of the EPSRC funded FACET project in collaboration with the UK National Museum of Science and Industry (NMSI) which includes the National Railway Museum. An export of NMSI's Collections Database is used as the dataset for the research. The J. Paul Getty Trust's Art and Architecture Thesaurus (AAT) is the main thesaurus in the project. The AAT is a widely used thesaurus (over 120,000 terms). Descriptors are organised in 7 facets representing separate conceptual classes of terms.The FACET application is a multi tiered architecture accessing a SQL Server database, with an OLE DB connection. The thesauri are stored as relational tables in the Server's database. However, a key component of the system is a parallel representation of the underlying semantic network as an in-memory structure of thesaurus concepts (corresponding to preferred terms). The structure models the hierarchical and associative interrelationships of thesaurus concepts via weighted poly-hierarchical links. Its primary purpose is real-time semantic expansion of query terms, achieved by a spreading activation semantic closeness algorithm. Queries with associated results are stored persistently using XML format data. A Visual Basic interface combines a thesaurus browser and an initial term search facility that takes into account equivalence relationships. Terms are dragged to a direct manipulation Query Builder which maintains the facet structure.
  18. Zhang, J.; Mostafa, J.; Tripathy, H.: Information retrieval by semantic analysis and visualization of the concept space of D-Lib® magazine (2002) 0.01
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  19. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.00
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
  20. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.00
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    Date
    22. 7.2006 17:56:22