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  • × theme_ss:"Retrievalalgorithmen"
  1. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.02
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  2. Crestani, F.: Combination of similarity measures for effective spoken document retrieval (2003) 0.02
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    Source
    Journal of information science. 29(2003) no.2, S.87-96
  3. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.02
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    Date
    30. 3.2001 13:32:22
    Source
    Computer journal. 26(1983), S.239-246
  4. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.02
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    Date
    25. 8.2005 17:42:22
    Source
    Library and information research news. 24(2000) no.77, S.30-34
  5. Okada, M.; Ando, K.; Lee, S.S.; Hayashi, Y.; Aoe, J.I.: ¬An efficient substring search method by using delayed keyword extraction (2001) 0.02
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    Date
    29. 3.2002 17:24:03
    Source
    Information processing and management. 37(2001) no.5, S.741-761
  6. Cole, C.: Intelligent information retrieval: diagnosing information need : Part II: uncertainty expansion in a prototype of a diagnostic IR tool (1998) 0.02
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    Date
    11. 8.2001 14:48:29
    Source
    Information processing and management. 34(1998) no.6, S.721-731
  7. Zhang, W.; Korf, R.E.: Performance of linear-space search algorithms (1995) 0.02
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    Date
    2. 8.1996 10:29:15
    Source
    Artificial intelligence. 79(1995) no.2, S.241-292
  8. Uratani, N.; Takeda, M.: ¬A fast string-searching algorithm for multiple patterns (1993) 0.01
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    Abstract
    The string-searching problem is to find all occurrences of pattern(s) in a text string. The Aho-Corasick string searching algorithm simultaneously finds all occurrences of multiple patterns in one pass through the text. The Boyer-Moore algorithm is the fastest algorithm for a single pattern. By combining the ideas of these two algorithms, presents an efficient string searching algorithm for multiple patterns. The algorithm runs in sublinear time, on the average, as the BM algorithm achieves, and its preprocessing time is linear proportional to the sum of the lengths of the patterns like the AC algorithm
    Source
    Information processing and management. 29(1993) no.6, S.775-791
  9. Thompson, P.: Looking back: on relevance, probabilistic indexing and information retrieval (2008) 0.01
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    Date
    31. 7.2008 19:58:29
    Source
    Information processing and management. 44(2008) no.2, S.963-970
  10. Vechtomova, O.; Karamuftuoglu, M.: Lexical cohesion and term proximity in document ranking (2008) 0.01
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    Date
    1. 8.2008 12:29:05
    Source
    Information processing and management. 44(2008) no.4, S.1485-1502
  11. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.01
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    Date
    20. 1.2007 18:30:22
    Source
    Aslib proceedings. 56(2004) no.4, S.201-211
  12. Faloutsos, C.: Signature files (1992) 0.01
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    Date
    7. 5.1999 15:22:48
    Pages
    S.44-65
  13. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.01
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    Date
    22. 3.2003 19:27:23
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.285-301
  14. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.01
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    Date
    22. 8.2014 17:05:18
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
  15. Paris, L.A.H.; Tibbo, H.R.: Freestyle vs. Boolean : a comparison of partial and exact match retrieval systems (1998) 0.01
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