Search (43 results, page 2 of 3)

  • × language_ss:"e"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Sanderson, M.; Lawrie, D.: Building, testing, and applying concept hierarchies (2000) 0.01 
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    Series
    The Kluwer international series on information retrieval; 7
  2. Fowler, R.H.; Wilson, B.A.; Fowler, W.A.L.: Information navigator : an information system using associative networks for display and retrieval (1992) 0.01 
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    Date
    7. 2.2013 19:00:19
  3. Evens, M.: Thesaural relations in information retrieval (2002) 0.01 
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    Date
    7. 9.1996 17:35:55
  4. Hovy, E.: Comparing sets of semantic relations in ontologies (2002) 0.01 
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    7. 9.1996 17:35:55
  5. Arenas, M.; Cuenca Grau, B.; Kharlamov, E.; Marciuska, S.; Zheleznyakov, D.: Faceted search over ontology-enhanced RDF data (2014) 0.01 
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    Date
    7. 9.2015 16:40:06
  6. Colace, F.; Santo, M. de; Greco, L.; Napoletano, P.: Improving relevance feedback-based query expansion by the use of a weighted word pairs approach (2015) 0.01 
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    Abstract
    In this article, the use of a new term extraction method for query expansion (QE) in text retrieval is investigated. The new method expands the initial query with a structured representation made of weighted word pairs (WWP) extracted from a set of training documents (relevance feedback). Standard text retrieval systems can handle a WWP structure through custom Boolean weighted models. We experimented with both the explicit and pseudorelevance feedback schemas and compared the proposed term extraction method with others in the literature, such as KLD and RM3. Evaluations have been conducted on a number of test collections (Text REtrivel Conference [TREC]-6, -7, -8, -9, and -10). Results demonstrated that the QE method based on this new structure outperforms the baseline.
  7. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01 
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    Date
    22. 2.1996 13:14:10
  8. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01 
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    Date
    22. 3.2003 19:35:46
  9. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.01 
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    Date
    22. 7.2006 16:32:43
  10. Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014) 0.01 
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    Date
    22. 8.2014 17:07:50
  11. Chen, H.; Lally, A.M.; Zhu, B.; Chau, M.: HelpfulMed : Intelligent searching for medical information over the Internet (2003) 0.01 
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    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.7, S.683-694
  12. Prasad, A.R.D.; Madalli, D.P.: Faceted infrastructure for semantic digital libraries (2008) 0.01 
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    Date
    7. 6.2008 18:47:03
  13. Bando, L.L.; Scholer, F.; Turpin, A.: Query-biased summary generation assisted by query expansion : temporality (2015) 0.01 
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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.
  14. Smith, D.A.; Shadbolt, N.R.: FacetOntology : expressive descriptions of facets in the Semantic Web (2012) 0.01 
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    Date
    7. 9.2015 17:09:55
  15. Xu, B.; Lin, H.; Lin, Y.: Assessment of learning to rank methods for query expansion (2016) 0.01 
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    Date
    7. 5.2016 13:13:43
  16. Ruotsalo, T.; Jacucci, G.; Kaski, S.: Interactive faceted query suggestion for exploratory search : whole-session effectiveness and interaction engagement (2020) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 71(2020) no.7, S.742-756
  17. Bradford, R.B.: Relationship discovery in large text collections using Latent Semantic Indexing (2006) 0.01 
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    Source
    Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]
  18. Brunetti, J.M.; Roberto García, R.: User-centered design and evaluation of overview components for semantic data exploration (2014) 0.01 
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    Date
    20. 1.2015 18:30:22
  19. 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.
  20. Agarwal, N.K.: Exploring context in information behavior : seeker, situation, surroundings, and shared identities (2018) 0.01 
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    Date
    7. 2.2019 10:51:07

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