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  • × theme_ss:"Retrievalstudien"
  1. Sanderson, M.: ¬The Reuters test collection (1996) 0.01
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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
  2. Lespinasse, K.: TREC: une conference pour l'evaluation des systemes de recherche d'information (1997) 0.01
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    Date
    1. 8.1996 22:01:00
  3. ¬The Fifth Text Retrieval Conference (TREC-5) (1997) 0.01
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    Abstract
    Proceedings of the 5th TREC-confrerence held in Gaithersburgh, Maryland, Nov 20-22, 1996. Aim of the conference was discussion on retrieval techniques for large test collections. Different research groups used different techniques, such as automated thesauri, term weighting, natural language techniques, relevance feedback and advanced pattern matching, for information retrieval from the same large database. This procedure makes it possible to compare the results. The proceedings include papers, tables of the system results, and brief system descriptions including timing and storage information
  4. Pemberton, J.K.; Ojala, M.; Garman, N.: Head to head : searching the Web versus traditional services (1998) 0.01
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    Source
    Online. 22(1998) no.3, S.24-26,28
  5. Dresel, R.; Hörnig, D.; Kaluza, H.; Peter, A.; Roßmann, A.; Sieber, W.: Evaluation deutscher Web-Suchwerkzeuge : Ein vergleichender Retrievaltest (2001) 0.01
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    Abstract
    Die deutschen Suchmaschinen, Abacho, Acoon, Fireball und Lycos sowie die Web-Kataloge Web.de und Yahoo! werden einem Qualitätstest nach relativem Recall, Precision und Availability unterzogen. Die Methoden der Retrievaltests werden vorgestellt. Im Durchschnitt werden bei einem Cut-Off-Wert von 25 ein Recall von rund 22%, eine Precision von knapp 19% und eine Verfügbarkeit von 24% erreicht
  6. Ellis, D.: Progress and problems in information retrieval (1996) 0.01
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    Date
    26. 7.2002 20:22:46
  7. ¬The Eleventh Text Retrieval Conference, TREC 2002 (2003) 0.01
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    Abstract
    Proceedings of the llth TREC-conference held in Gaithersburg, Maryland (USA), November 19-22, 2002. Aim of the conference was discussion an retrieval and related information-seeking tasks for large test collection. 93 research groups used different techniques, for information retrieval from the same large database. This procedure makes it possible to compare the results. The tasks are: Cross-language searching, filtering, interactive searching, searching for novelty, question answering, searching for video shots, and Web searching.
  8. Blagden, J.F.: How much noise in a role-free and link-free co-ordinate indexing system? (1966) 0.01
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    Source
    Journal of documentation. 22(1966), S.203-209
  9. Smithson, S.: Information retrieval evaluation in practice : a case study approach (1994) 0.01
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    Abstract
    The evaluation of information retrieval systems is an important yet difficult operation. This paper describes an exploratory evaluation study that takes an interpretive approach to evaluation. The longitudinal study examines evaluation through the information-seeking behaviour of 22 case studies of 'real' users. The eclectic approach to data collection produced behavioral data that is compared with relevance judgements and satisfaction ratings. The study demonstrates considerable variations among the cases, among different evaluation measures within the same case, and among the same measures at different stages within a single case. It is argued that those involved in evaluation should be aware of the difficulties, and base any evaluation on a good understanding of the cases in question
  10. Blair, D.C.: STAIRS Redux : thoughts on the STAIRS evaluation, ten years after (1996) 0.01
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    Source
    Journal of the American Society for Information Science. 47(1996) no.1, S.4-22
  11. Losee, R.M.: Determining information retrieval and filtering performance without experimentation (1995) 0.01
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    Date
    22. 2.1996 13:14:10
  12. Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983) 0.01
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    Date
    14. 3.1996 13:22:21
  13. Brown, M.E.: By any other name : accounting for failure in the naming of subject categories (1995) 0.01
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    Date
    2.11.1996 13:08:22
  14. Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002) 0.01
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  15. Oberhauser, O.; Labner, J.: OPAC-Erweiterung durch automatische Indexierung : Empirische Untersuchung mit Daten aus dem Österreichischen Verbundkatalog (2002) 0.01
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    Abstract
    In Anlehnung an die in den neunziger Jahren durchgeführten Erschließungsprojekte MILOS I und MILOS II, die die Eignung eines Verfahrens zur automatischen Indexierung für Bibliothekskataloge zum Thema hatten, wurde eine empirische Untersuchung anhand einer repräsentativen Stichprobe von Titelsätzen aus dem Österreichischen Verbundkatalog durchgeführt. Ziel war die Prüfung und Bewertung der Einsatzmöglichkeit dieses Verfahrens in den Online-Katalogen des Verbundes. Der Realsituation der OPAC-Benutzung gemäß wurde ausschließlich die Auswirkung auf den automatisch generierten Begriffen angereicherten Basic Index ("Alle Felder") untersucht. Dazu wurden 100 Suchanfragen zunächst im ursprünglichen Basic Index und sodann im angereicherten Basic Index in einem OPAC unter Aleph 500 durchgeführt. Die Tests erbrachten einen Zuwachs an relevanten Treffern bei nur leichten Verlusten an Precision, eine Reduktion der Nulltreffer-Ergebnisse sowie Aufschlüsse über die Auswirkung einer vorhandenen verbalen Sacherschließung.
  16. Rokaya, M.; Atlam, E.; Fuketa, M.; Dorji, T.C.; Aoe, J.-i.: Ranking of field association terms using Co-word analysis (2008) 0.01
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  17. Baillie, M.; Azzopardi, L.; Ruthven, I.: Evaluating epistemic uncertainty under incomplete assessments (2008) 0.01
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  18. Lioma, C.; Ounis, I.: ¬A syntactically-based query reformulation technique for information retrieval (2008) 0.01
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    Abstract
    Whereas in language words of high frequency are generally associated with low content [Bookstein, A., & Swanson, D. (1974). Probabilistic models for automatic indexing. Journal of the American Society of Information Science, 25(5), 312-318; Damerau, F. J. (1965). An experiment in automatic indexing. American Documentation, 16, 283-289; Harter, S. P. (1974). A probabilistic approach to automatic keyword indexing. PhD thesis, University of Chicago; Sparck-Jones, K. (1972). A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28, 11-21; Yu, C., & Salton, G. (1976). Precision weighting - an effective automatic indexing method. Journal of the Association for Computer Machinery (ACM), 23(1), 76-88], shallow syntactic fragments of high frequency generally correspond to lexical fragments of high content [Lioma, C., & Ounis, I. (2006). Examining the content load of part of speech blocks for information retrieval. In Proceedings of the international committee on computational linguistics and the association for computational linguistics (COLING/ACL 2006), Sydney, Australia]. We implement this finding to Information Retrieval, as follows. We present a novel automatic query reformulation technique, which is based on shallow syntactic evidence induced from various language samples, and used to enhance the performance of an Information Retrieval system. Firstly, we draw shallow syntactic evidence from language samples of varying size, and compare the effect of language sample size upon retrieval performance, when using our syntactically-based query reformulation (SQR) technique. Secondly, we compare SQR to a state-of-the-art probabilistic pseudo-relevance feedback technique. Additionally, we combine both techniques and evaluate their compatibility. We evaluate our proposed technique across two standard Text REtrieval Conference (TREC) English test collections, and three statistically different weighting models. Experimental results suggest that SQR markedly enhances retrieval performance, and is at least comparable to pseudo-relevance feedback. Notably, the combination of SQR and pseudo-relevance feedback further enhances retrieval performance considerably. These collective experimental results confirm the tenet that high frequency shallow syntactic fragments correspond to content-bearing lexical fragments.
  19. Sievert, M.E.; McKinin, E.J.: Why full-text misses some relevant documents : an analysis of documents not retrieved by CCML or MEDIS (1989) 0.01
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    Date
    9. 1.1996 10:22:31
  20. Wood, F.; Ford, N.; Miller, D.; Sobczyk, G.; Duffin, R.: Information skills, searching behaviour and cognitive styles for student-centred learning : a computer-assisted learning approach (1996) 0.01
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    Source
    Journal of information science. 22(1996) no.2, S.79-92

Languages

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  • d 5
  • f 1
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Types

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  • s 3
  • m 2
  • r 1
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