Search (98 results, page 5 of 5)

  • × theme_ss:"Retrievalalgorithmen"
  • × year_i:[1990 TO 2000}
  1. Courtois, M.P.; Berry, M.W.: Results ranking in Web search engines (1999) 0.00 
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  2. Rada, R.; Barlow, J.; Potharst, J.; Zanstra, P.; Bijstra, D.: Document ranking using an enriched thesaurus (1991) 0.00 
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    Abstract
    A thesaurus may be viewed as a graph, and document retrieval algorithms can exploit this graph when both the documents and the query are represented by thesaurus terms. These retrieval algorithms measure the distance between the query and documents by using the path lengths in the graph. Previous work witj such strategies has shown that the hierarchical relations in the thesaurus are useful but the non-hierarchical are not. This paper shows that when the query explicitly mentions a particular non-hierarchical relation, the retrieval algorithm benefits from the presence of such relations in the thesaurus. Our algorithms were applied to the Excerpta Medica bibliographic citation database whose citations are indexed with terms from the EMTREE thesaurus. We also created an enriched EMTREE by systematically adding non-hierarchical relations from a medical knowledge base. Our algorithms used at one time EMTREE and, at another time, the enriched EMTREE in the course of ranking documents from Excerpta Medica against queries. When, and only when, the query specifically mentioned a particular non-hierarchical relation type, did EMTREE enriched with that relation type lead to a ranking that better corresponded to an expert's ranking
  3. Lalmas, M.; Ruthven, I.: Representing and retrieving structured documents using the Dempster-Shafer theory of evidence : modelling and evaluation (1998) 0.00 
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    Abstract
    Reports on a theoretical model of structured document indexing and retrieval based on the Dempster-Schafer Theory of Evidence. Includes a description of the model of structured document retrieval, the representation of structured documents, the representation of individual components, how components are combined, details of the combination process, and how relevance is captured within the model. Also presents a detailed account of an implementation of the model, and an evaluation scheme designed to test the effectiveness of the model
  4. Chakrabarti, S.; Dom, B.; Kumar, S.R.; Raghavan, P.; Rajagopalan, S.; Tomkins, A.; Kleinberg, J.M.; Gibson, D.: Neue Pfade durch den Internet-Dschungel : Die zweite Generation von Web-Suchmaschinen (1999) 0.00 
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  5. Al-Hawamdeh, S.; Smith, G.; Willett, P.; Vere, R. de: Using nearest-neighbour searching techniques to access full-text documents (1991) 0.00 
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    Abstract
    Summarises the results to date of a continuing programme of research at Sheffield Univ. to investigate the use of nearest-neighbour retrieval algorithms for full text searching. Given a natural language query statement, the research methods result in a ranking of the paragraphs comprising a full text document in order of decreasing similarity with the query, where the similarity for each paragraph is determined by the number of keyword stems that it has in common with the query
  6. Chang, R.: Keyword searching and indexing (1993) 0.00 
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    Abstract
    Explains how a computer indexing system works. Reviews fundamentals of how data are stored and retrieved by computers. Describes B-Tree and B+-Tree indexing structures. Gives basic keyword searching techniques that the user must apply to make use of the indexing programs. The demand for keyword retrieval is increasing and librarians should expect to see the keyword-indexing feature become commonly available
  7. Hancock-Beaulieu, M.; Walker, S.: ¬An evaluation of automatic query expansion in an online library catalogue (1992) 0.00 
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  8. Davis, C.H.: Beyond Boole : the next logical step (1995) 0.00 
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    Source
    Bulletin of the American Society for Information Science. 21(1995), S.17-20
  9. Koyama, M.: ¬A fast retrieving algorithm of hierarchical relationships using tree structures (1998) 0.00 
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    Source
    Information processing and management. 34(1998) no.6, S.761-763
  10. Schamber, L.; Bateman, J.: Relevance criteria uses and importance : progress in development of a measurement scale (1999) 0.00 
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    Abstract
    The criteria employed by end-users in making relevance judgments can be powerful and useful indicators of the values users ascribe to a variety of factors in their information seeking and use situations. This paper describes intermediate results in a long-term project intended to develop a measurement scale based on users' relevance criteria. The five tests that are reported here have involved 350 users in an effort to progressively refine and validate the scale content. The range of research questions and types of users and information environments have gradually been expanded to assess the adaptability and transferability of the instrument. The instrument provides quantitative data, notably criterion importance ratings that can be analyzed using several techniques. The substantive findings confirm those of previous studies on relevance evaluation behavior
    Imprint
    Medford, NJ : Information Today
    Series
    Proceedings of the American Society for Information Science; vol.36
    Source
    Knowledge: creation, organization and use. Proceedings of the 62nd Annual Meeting of the American Society for Information Science, 31.10.-4.11.1999. Ed.: L. Woods
  11. Quint, B.: Check out the new RANK command on DIALOG (1993) 0.00 
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    Abstract
    Describes the RANK command on DIALOG online information service. RANK conducts statistical analysis on an existing set of search results for fields specified by searchers. Details how to use RANK and applications. Points out drawbacks to its use
  12. Ruthven, I.; Lalmas, M.: Selective relevance feedback using term characteristics (1999) 0.00 
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    Source
    Vocabulary as a central concept in digital libraries: interdisciplinary concepts, challenges, and opportunities : proceedings of the Third International Conference an Conceptions of Library and Information Science (COLIS3), Dubrovnik, Croatia, 23-26 May 1999. Ed. by T. Arpanac et al
  13. Uratani, N.; Takeda, M.: ¬A fast string-searching algorithm for multiple patterns (1993) 0.00 
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    Source
    Information processing and management. 29(1993) no.6, S.775-791
  14. Couvreur, T.R.; Benzel, R.N.; Miller, S.F.; Zeitler, D.N.; Lee, D.L.; Singhal, M.; Shivaratri, N.; Wong, W.Y.P.: ¬An analysis of performance and cost factors in searching large text databases using parallel search systems (1994) 0.00 
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    Source
    Journal of the American Society for Information Science. 45(1994) no.7, S.443-464
  15. Smith, M.P.; Pollitt, S.A.: ¬A comparison of ranking formulae and their ranks (1995) 0.00 
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    Abstract
    Reports a study to compare the ranking produced by several well known probabilistic formulae. Values for the variables used in these formulae (collection frequency for a query term, number of relevant documents retrieved, and number of relevant documents retrieved, and number of relevant documents indexed by the query term) were derived using a random number generator, the number of documents in the collection was fixed at 500.000. This produced ranked bands for each formula using document term characteristics rather than actual documents. These rankings were compared with one another using the Spearman Rho ranked correlation co-efficient to determine how closely the algorithms rank documents. There is little difference in the rankings produced by the Expected Mutual Information measure EMIM and the simpler F4.5 weighting scheme
  16. Evans, R.: Beyond Boolean : relevance ranking, natural language and the new search paradigm (1994) 0.00 
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    Imprint
    Medford, NJ : Learned Information
  17. Moffat, A.; Bell, T.A.H.: In situ generation of compressed inverted files (1995) 0.00 
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    Source
    Journal of the American Society for Information Science. 46(1995) no.7, S.537-550
  18. Green, R.: Topical relevance relationships : 2: an exploratory study and preliminary typology (1995) 0.00 
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    Source
    Journal of the American Society for Information Science. 46(1995) no.9, S.654-662

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