Search (16 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Retrievalalgorithmen"
  • × year_i:[1990 TO 2000}
  1. 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
  2. Cole, C.: Intelligent information retrieval: diagnosing information need : Part II: uncertainty expansion in a prototype of a diagnostic IR tool (1998) 0.00 
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    Date
    11. 8.2001 14:48:29
  3. Frants, V.I.; Shapiro, J.: Control and feedback in a documentary information retrieval system (1991) 0.00 
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    Abstract
    Addresses the problem of control in documentary information retrieval systems is analysed and it is shown why an IR system has to be looked at as an adaptive system. The algorithms of feedback are proposed and it is shown how they depend on the type of the collection of documents: static (no change in the collection between searches) and dynamic (when the change occurs between searches). The proposed algorithms are the basis for the development of the fully automated information retrieval systems
  4. Smith, M.; Smith, M.P.; Wade, S.J.: Applying genetic programming to the problem of term weight algorithms (1995) 0.00 
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  5. Zhang, W.; Korf, R.E.: Performance of linear-space search algorithms (1995) 0.00 
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    Date
    2. 8.1996 10:29:15
  6. Faloutsos, C.: Signature files (1992) 0.00 
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    Date
    7. 5.1999 15:22:48
  7. Kantor, P.; Kim, M.H.; Ibraev, U.; Atasoy, K.: Estimating the number of relevant documents in enormous collections (1999) 0.00 
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    Abstract
    In assessing information retrieval systems, it is important to know not only the precision of the retrieved set, but also to compare the number of retrieved relevant items to the total number of relevant items. For large collections, such as the TREC test collections, or the World Wide Web, it is not possible to enumerate the entire set of relevant documents. If the retrieved documents are evaluated, a variant of the statistical "capture-recapture" method can be used to estimate the total number of relevant documents, providing the several retrieval systems used are sufficiently independent. We show that the underlying signal detection model supporting such an analysis can be extended in two ways. First, assuming that there are two distinct performance characteristics (corresponding to the chance of retrieving a relevant, and retrieving a given non-relevant document), we show that if there are three or more independent systems available it is possible to estimate the number of relevant documents without actually having to decide whether each individual document is relevant. We report applications of this 3-system method to the TREC data, leading to the conclusion that the independence assumptions are not satisfied. We then extend the model to a multi-system, multi-problem model, and show that it is possible to include statistical dependencies of all orders in the model, and determine the number of relevant documents for each of the problems in the set. Application to the TREC setting will be presented
  8. Paris, L.A.H.; Tibbo, H.R.: Freestyle vs. Boolean : a comparison of partial and exact match retrieval systems (1998) 0.00 
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    Date
    12. 3.1999 10:29:27
  9. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.00 
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    Date
    1. 8.1996 22:08:06
  10. Moffat, A.; Bell, T.A.H.: In situ generation of compressed inverted files (1995) 0.00 
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    Date
    27.11.1995 21:29:58
  11. Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995) 0.00 
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    Date
    29. 1.1996 18:42:14
  12. Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996) 0.00 
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    Date
    12. 9.1996 13:56:22
  13. Kelledy, F.; Smeaton, A.F.: Signature files and beyond (1996) 0.00 
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  14. Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995) 0.00 
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    Date
    22. 2.1996 11:20:06
  15. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.00 
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    Date
    22. 2.1996 13:14:10
  16. Cross-language information retrieval (1998) 0.00 
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    Content
    Enthält die Beiträge: GREFENSTETTE, G.: The Problem of Cross-Language Information Retrieval; DAVIS, M.W.: On the Effective Use of Large Parallel Corpora in Cross-Language Text Retrieval; BALLESTEROS, L. u. W.B. CROFT: Statistical Methods for Cross-Language Information Retrieval; Distributed Cross-Lingual Information Retrieval; Automatic Cross-Language Information Retrieval Using Latent Semantic Indexing; EVANS, D.A. u.a.: Mapping Vocabularies Using Latent Semantics; PICCHI, E. u. C. PETERS: Cross-Language Information Retrieval: A System for Comparable Corpus Querying; YAMABANA, K. u.a.: A Language Conversion Front-End for Cross-Language Information Retrieval; GACHOT, D.A. u.a.: The Systran NLP Browser: An Application of Machine Translation Technology in Cross-Language Information Retrieval; HULL, D.: A Weighted Boolean Model for Cross-Language Text Retrieval; SHERIDAN, P. u.a. Building a Large Multilingual Test Collection from Comparable News Documents; OARD; D.W. u. B.J. DORR: Evaluating Cross-Language Text Filtering Effectiveness

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