Search (128 results, page 1 of 7)

  • × theme_ss:"Retrievalalgorithmen"
  1. Salton, G.; Buckley, C.: Term-weighting approaches in automatic text retrieval (1988) 0.06
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.323-328.
  2. Salton, G.; Buckley, C.: Parallel text search methods (1988) 0.04
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  3. Information retrieval : data structures and algorithms (1992) 0.04
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    Content
    An edited volume containing data structures and algorithms for information retrieval including a disk with examples written in C. for prgrammers and students interested in parsing text, automated indexing, its the first collection in book form of the basic data structures and algorithms that are critical to the storage and retrieval of documents. ------------------Enthält die Kapitel: FRAKES, W.B.: Introduction to information storage and retrieval systems; BAEZA-YATES, R.S.: Introduction to data structures and algorithms related to information retrieval; HARMAN, D. u.a.: Inverted files; FALOUTSOS, C.: Signature files; GONNET, G.H. u.a.: New indices for text: PAT trees and PAT arrays; FORD, D.A. u. S. CHRISTODOULAKIS: File organizations for optical disks; FOX, C.: Lexical analysis and stoplists; FRAKES, W.B.: Stemming algorithms; SRINIVASAN, P.: Thesaurus construction; BAEZA-YATES, R.A.: String searching algorithms; HARMAN, D.: Relevance feedback and other query modification techniques; WARTIK, S.: Boolean operators; WARTIK, S. u.a.: Hashing algorithms; HARMAN, D.: Ranking algorithms; FOX, E.: u.a.: Extended Boolean models; RASMUSSEN, E.: Clustering algorithms; HOLLAAR, L.: Special-purpose hardware for information retrieval; STANFILL, C.: Parallel information retrieval algorithms
    Editor
    Frakes, W.B. u. R. Baeza-Yates
    Footnote
    Rez. in: Computing reviews. July 1993, S.341-342 (G. Salton)
  4. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.03
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    Date
    1. 8.1996 22:08:06
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  5. Faloutsos, C.: Signature files (1992) 0.03
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    Date
    7. 5.1999 15:22:48
    Source
    Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
  6. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.03
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    Date
    16.11.2008 16:22:48
    Source
    Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  7. Iker, H.P.: Solution of Boolean equations through the use of term weights to the base two (1967) 0.03
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  8. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.03
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    Date
    14. 6.2015 22:12:56
    Source
    Automatische Indexierung zwischen Forschung und Anwendung, Hrsg.: G. Lustig
  9. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.03
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    Date
    30. 3.2001 13:32:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  10. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.02
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    Abstract
    The study reported here investigated the query expansion behavior of end-users interacting with a thesaurus-enhanced search system on the Web. Two groups, namely academic staff and postgraduate students, were recruited into this study. Data were collected from 90 searches performed by 30 users using the OVID interface to the CAB abstracts database. Data-gathering techniques included questionnaires, screen capturing software, and interviews. The results presented here relate to issues of search-topic and search-term characteristics, number and types of expanded queries, usefulness of thesaurus terms, and behavioral differences between academic staff and postgraduate students in their interaction. The key conclusions drawn were that (a) academic staff chose more narrow and synonymous terms than did postgraduate students, who generally selected broader and related terms; (b) topic complexity affected users' interaction with the thesaurus in that complex topics required more query expansion and search term selection; (c) users' prior topic-search experience appeared to have a significant effect on their selection and evaluation of thesaurus terms; (d) in 50% of the searches where additional terms were suggested from the thesaurus, users stated that they had not been aware of the terms at the beginning of the search; this observation was particularly noticeable in the case of postgraduate students.
    Date
    22. 7.2006 16:32:43
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  11. Cross-language information retrieval (1998) 0.02
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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
    Editor
    Grefenstette, G.
  12. Carpineto, C.; Romano, G.: Information retrieval through hybrid navigation of lattice representations (1996) 0.02
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  13. Frakes, W.B.: Stemming algorithms (1992) 0.02
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    Abstract
    Desribes stemming algorithms - programs that relate morphologically similar indexing and search terms. Stemming is used to improve retrieval effectiveness and to reduce the size of indexing files. Several approaches to stemming are describes - table lookup, affix removal, successor variety, and n-gram. empirical studies of stemming are summarized. The Porter stemmer is described in detail, and a full implementation in C is presented
    Source
    Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
  14. Stanfill, C.: Parallel information retrieval algorithms (1992) 0.02
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    Source
    Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
  15. Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014) 0.01
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    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  16. Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000) 0.01
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    Source
    Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al
  17. Wu, H.; Salton, G.: ¬The estimation of term relevance weights using relevance feedback (1981) 0.01
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  18. Salton, G.: ¬A simple blueprint for automatic Boolean query processing (1988) 0.01
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  19. Carpineto, C.; Romano, G.: Order-theoretical ranking (2000) 0.01
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  20. Dannenberg, R.B.; Birmingham, W.P.; Pardo, B.; Hu, N.; Meek, C.; Tzanetakis, G.: ¬A comparative evaluation of search techniques for query-by-humming using the MUSART testbed (2007) 0.01
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Languages

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Types

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