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  • × theme_ss:"Retrievalstudien"
  1. Rajagopal, P.; Ravana, S.D.; Koh, Y.S.; Balakrishnan, V.: Evaluating the effectiveness of information retrieval systems using effort-based relevance judgment (2019) 0.05 
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    Date
    20. 1.2015 18:30:22
  2. Lohmann, H.: Verbesserung der Literatursuche durch Dokumentanreicherung und automatische Inhaltserschließung : Das Projekt 'KASCADE' an der Universitäts- und Landesbibliothek Düsseldorf (1999) 0.04 
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    Pages
    V,117,14 S
  3. 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
  4. Chen, H.; Dhar, V.: Cognitive process as a basis for intelligent retrieval system design (1991) 0.03 
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  5. Jochum, F.; Weissmann, V.: Struktur und Elemente des Information Retrieval Experiments (1985) 0.03 
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  6. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.02 
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    Date
    20.10.2000 12:22:23
  7. 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
  8. 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
  9. 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
  10. 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."
  11. Della Mea, V.; Mizzaro, S.: Measuring retrieval effectiveness : a new proposal and a first experimental validation (2004) 0.02 
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  12. López-Ostenero, F.; Peinado, V.; Gonzalo, J.; Verdejo, F.: Interactive question answering : Is Cross-Language harder than monolingual searching? (2008) 0.02 
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  13. Petras, V.; Womser-Hacker, C.: Evaluation im Information Retrieval (2023) 0.02 
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  14. Allan, J.; Callan, J.P.; Croft, W.B.; Ballesteros, L.; Broglio, J.; Xu, J.; Shu, H.: INQUERY at TREC-5 (1997) 0.02 
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    Date
    27. 2.1999 20:55:22
  15. Ng, K.B.; Loewenstern, D.; Basu, C.; Hirsh, H.; Kantor, P.B.: Data fusion of machine-learning methods for the TREC5 routing tak (and other work) (1997) 0.02 
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    Date
    27. 2.1999 20:59:22
  16. Saracevic, T.: On a method for studying the structure and nature of requests in information retrieval (1983) 0.02 
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    Pages
    S.22-25
  17. Angelini, M.; Fazzini, V.; Ferro, N.; Santucci, G.; Silvello, G.: CLAIRE: A combinatorial visual analytics system for information retrieval evaluation (2018) 0.02 
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  18. White, H.D.: Relevance theory and distributions of judgments in document retrieval (2017) 0.02 
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    Abstract
    This article extends relevance theory (RT) from linguistic pragmatics into information retrieval. Using more than 50 retrieval experiments from the literature as examples, it applies RT to explain the frequency distributions of documents on relevance scales with three or more points. The scale points, which judges in experiments must consider in addition to queries and documents, are communications from researchers. In RT, the relevance of a communication varies directly with its cognitive effects and inversely with the effort of processing it. Researchers define and/or label the scale points to measure the cognitive effects of documents on judges. However, they apparently assume that all scale points as presented are equally easy for judges to process. Yet the notion that points cost variable effort explains fairly well the frequency distributions of judgments across them. By hypothesis, points that cost more effort are chosen by judges less frequently. Effort varies with the vagueness or strictness of scale-point labels and definitions. It is shown that vague scales tend to produce U- or V-shaped distributions, while strict scales tend to produce right-skewed distributions. These results reinforce the paper's more general argument that RT clarifies the concept of relevance in the dialogues of retrieval evaluation.
  19. Rijsbergen, C.J. van: ¬A test for the separation of relevant and non-relevant documents in experimental retrieval collections (1973) 0.01 
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    Date
    19. 3.1996 11:22:12
  20. 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

Authors

Years

Languages

  • e 53
  • d 6
  • f 1
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Types

  • a 54
  • s 5
  • m 4
  • el 1
  • x 1
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Themes

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Classifications