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  • × theme_ss:"Retrievalstudien"
  1. Sanderson, M.: ¬The Reuters test collection (1996) 0.05 
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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. Dresel, R.; Hörnig, D.; Kaluza, H.; Peter, A.; Roßmann, A.; Sieber, W.: Evaluation deutscher Web-Suchwerkzeuge : Ein vergleichender Retrievaltest (2001) 0.05 
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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
  3. 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) 0.04 
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    Source
    Journal of information science. 22(1996) no.2, S.79-92
  4. Crestani, F.; Rijsbergen, C.J. van: Information retrieval by imaging (1996) 0.04 
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    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
  5. Pal, S.; Mitra, M.; Kamps, J.: Evaluation effort, reliability and reusability in XML retrieval (2011) 0.04 
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    Abstract
    The Initiative for the Evaluation of XML retrieval (INEX) provides a TREC-like platform for evaluating content-oriented XML retrieval systems. Since 2007, INEX has been using a set of precision-recall based metrics for its ad hoc tasks. The authors investigate the reliability and robustness of these focused retrieval measures, and of the INEX pooling method. They explore four specific questions: How reliable are the metrics when assessments are incomplete, or when query sets are small? What is the minimum pool/query-set size that can be used to reliably evaluate systems? Can the INEX collections be used to fairly evaluate "new" systems that did not participate in the pooling process? And, for a fixed amount of assessment effort, would this effort be better spent in thoroughly judging a few queries, or in judging many queries relatively superficially? The authors' findings validate properties of precision-recall-based metrics observed in document retrieval settings. Early precision measures are found to be more error-prone and less stable under incomplete judgments and small topic-set sizes. They also find that system rankings remain largely unaffected even when assessment effort is substantially (but systematically) reduced, and confirm that the INEX collections remain usable when evaluating nonparticipating systems. Finally, they observe that for a fixed amount of effort, judging shallow pools for many queries is better than judging deep pools for a smaller set of queries. However, when judging only a random sample of a pool, it is better to completely judge fewer topics than to partially judge many topics. This result confirms the effectiveness of pooling methods.
    Date
    22. 1.2011 14:20:56
  6. Cuadra, C.A.; Katter, R.V.: Experimental studies of relevance judgements: final report : Vol.2: description of individual studies (1967) 0.03 
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  7. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.02 
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    Date
    20.10.2000 12:22:23
  8. Tomaiuolo, N.G.; Parker, J.: Maximizing relevant retrieval : keyword and natural language searching (1998) 0.02 
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    Source
    Online. 22(1998) no.6, S.57-58
  9. Voorhees, E.M.; Harman, D.: Overview of the Sixth Text REtrieval Conference (TREC-6) (2000) 0.02 
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    Date
    11. 8.2001 16:22:19
  10. Dalrymple, P.W.: Retrieval by reformulation in two library catalogs : toward a cognitive model of searching behavior (1990) 0.02 
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    Date
    22. 7.2006 18:43:54
  11. Robertson, S.E.; Thompson, C.L.: ¬An operational evaluation of weighting, ranking and relevance feedback via a front-end system (1987) 0.02 
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  12. Hancock-Beaulieu, M.; McKenzie, L.; Irving, A.: Evaluative protocols for searching behaviour in online library catalogues (1991) 0.02 
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  13. Grunder, R.: Qualitätskriterien für Datenbanken : Grundsätzliche Überlegungen und Untersuchung ausgewählter Aspekte am Beispiel bibliographischer Online-Datenbanken (1995) 0.02 
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  14. Voorbij, H.: Titelwoorden - trefwoorden : een vergelijkend onderzoek (1997) 0.02 
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  15. Krause, J.; Mutschke, P.: Indexierung und Fulcrum-Evaluierung (1999) 0.02 
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  16. Aitchison, T.M.: Comparative evaluation of index languages : Part I, Design. Part II, Results (1969) 0.02 
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  17. TREC: experiment and evaluation in information retrieval (2005) 0.02 
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    Content
    Enthält die Beiträge: 1. The Text REtrieval Conference - Ellen M. Voorhees and Donna K. Harman 2. The TREC Test Collections - Donna K. Harman 3. Retrieval System Evaluation - Chris Buckley and Ellen M. Voorhees 4. The TREC Ad Hoc Experiments - Donna K. Harman 5. Routing and Filtering - Stephen Robertson and Jamie Callan 6. The TREC Interactive Tracks: Putting the User into Search - Susan T. Dumais and Nicholas J. Belkin 7. Beyond English - Donna K. Harman 8. Retrieving Noisy Text - Ellen M. Voorhees and John S. Garofolo 9.The Very Large Collection and Web Tracks - David Hawking and Nick Craswell 10. Question Answering in TREC - Ellen M. Voorhees 11. The University of Massachusetts and a Dozen TRECs - James Allan, W. Bruce Croft and Jamie Callan 12. How Okapi Came to TREC - Stephen Robertson 13. The SMART Project at TREC - Chris Buckley 14. Ten Years of Ad Hoc Retrieval at TREC Using PIRCS - Kui-Lam Kwok 15. MultiText Experiments for TREC - Gordon V. Cormack, Charles L. A. Clarke, Christopher R. Palmer and Thomas R. Lynam 16. A Language-Modeling Approach to TREC - Djoerd Hiemstra and Wessel Kraaij 17. BM Research Activities at TREC - Eric W. Brown, David Carmel, Martin Franz, Abraham Ittycheriah, Tapas Kanungo, Yoelle Maarek, J. Scott McCarley, Robert L. Mack, John M. Prager, John R. Smith, Aya Soffer, Jason Y. Zien and Alan D. Marwick Epilogue: Metareflections on TREC - Karen Sparck Jones
    Footnote
    ... TREC: Experiment and Evaluation in Information Retrieval is a reliable and comprehensive review of the TREC program and has been adopted by NIST as the official history of TREC (see http://trec.nist.gov). We were favorably surprised by the book. Well structured and written, chapters are self-contained and the existence of references to specialized and more detailed publications is continuous, which makes it easier to expand into the different aspects analyzed in the text. This book succeeds in compiling TREC evolution from its inception in 1992 to 2003 in an adequate and manageable volume. Thanks to the impressive effort performed by the authors and their experience in the field, it can satiate the interests of a great variety of readers. While expert researchers in the IR field and IR-related industrial companies can use it as a reference manual, it seems especially useful for students and non-expert readers willing to approach this research area. Like NIST, we would recommend this reading to anyone who may be interested in textual information retrieval."
  18. Burnett, M.; Fisher, C.; Jones, R.: InTEXT precision indexing in TREC4 (1996) 0.02 
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    Date
    27. 2.1999 20:55:22

Authors

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