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  • × theme_ss:"Retrievalstudien"
  1. 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) 0.05 
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    Source
    Journal of information science. 22(1996) no.2, S.79-92
  2. 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
  3. Salton, G.: ¬The Smart environment for retrieval systeme valuation : advantages and problem areas (1981) 0.03 
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  4. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.02 
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    Date
    20.10.2000 12:22:23
  5. 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
  6. 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
  7. 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
  8. Salton, G.; Lesk, M.E.: Computer evaluation of indexing and text processing (1968) 0.02 
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  9. Buckley, C.; Singhal, A.; Mitra, M.; Salton, G.: New retrieval approaches using SMART : TREC 4 (1996) 0.02 
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  10. Sheridan, P.; Ballerini, J.P.; Schäuble, P.: Building a large multilingual test collection from comparable news documents (1998) 0.02 
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    Source
    Cross-language information retrieval. Ed.: G. Grefenstette
  11. Davis, M.W.: On the effective use of large parallel corpora in cross-language text retrieval (1998) 0.02 
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    Source
    Cross-language information retrieval. Ed.: G. Grefenstette
  12. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.02 
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    Abstract
    Retrieval Tests sind die anerkannteste Methode, um neue Verfahren der Inhaltserschließung gegenüber traditionellen Verfahren zu rechtfertigen. Im Rahmen einer Diplomarbeit wurden zwei grundsätzlich unterschiedliche Systeme der automatischen inhaltlichen Erschließung anhand der Pressedatenbank des Verlagshauses Gruner + Jahr (G+J) getestet und evaluiert. Untersucht wurde dabei natürlichsprachliches Retrieval im Vergleich zu Booleschem Retrieval. Bei den beiden Systemen handelt es sich zum einen um Autonomy von Autonomy Inc. und DocCat, das von IBM an die Datenbankstruktur der G+J Pressedatenbank angepasst wurde. Ersteres ist ein auf natürlichsprachlichem Retrieval basierendes, probabilistisches System. DocCat demgegenüber basiert auf Booleschem Retrieval und ist ein lernendes System, das auf Grund einer intellektuell erstellten Trainingsvorlage indexiert. Methodisch geht die Evaluation vom realen Anwendungskontext der Textdokumentation von G+J aus. Die Tests werden sowohl unter statistischen wie auch qualitativen Gesichtspunkten bewertet. Ein Ergebnis der Tests ist, dass DocCat einige Mängel gegenüber der intellektuellen Inhaltserschließung aufweist, die noch behoben werden müssen, während das natürlichsprachliche Retrieval von Autonomy in diesem Rahmen und für die speziellen Anforderungen der G+J Textdokumentation so nicht einsetzbar ist
  13. 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.
    Footnote
    The retrieved output from a query including the phrase 'big rockets' may be, for instance, a sentence containing 'giant rocket' which is semantically ranked above 'military ocket'. David Hull (Xerox Research Centre, Grenoble) describes an implementation of a weighted Boolean model for Spanish-English CLIR. Users construct Boolean-type queries, weighting each term in the query, which is then translated by an on-line dictionary before being applied to the database. Comparisons with the performance of unweighted free-form queries ('vector space' models) proved encouraging. Two contributions consider the evaluation of CLIR systems. In order to by-pass the time-consuming and expensive process of assembling a standard collection of documents and of user queries against which the performance of an CLIR system is manually assessed, Páriac Sheridan et al (ETH Zurich) propose a method based on retrieving 'seed documents'. This involves identifying a unique document in a database (the 'seed document') and, for a number of queries, measuring how fast it is retrieved. The authors have also assembled a large database of multilingual news documents for testing purposes. By storing the (fairly short) documents in a structured form tagged with descriptor codes (e.g. for topic, country and area), the test suite is easily expanded while remaining consistent for the purposes of testing. Douglas Ouard and Bonne Dorr (University of Maryland) describe an evaluation methodology which appears to apply LSI techniques in order to filter and rank incoming documents designed for testing CLIR systems. The volume provides the reader an excellent overview of several projects in CLIR. It is well supported with references and is intended as a secondary text for researchers and practitioners. It highlights the need for a good, general tutorial introduction to the field."
  14. Blair, D.C.; Maron, M.E.: ¬An evaluation of retrieval effectiveness for a full-text document-retrieval system (1985) 0.02 
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    Footnote
    Vgl. auch : Salton, G.: Another look ... Comm. ACM 29(1986) S.S.648-656; Blair, D.C.: Full text retrieval ... Int. Class. 13(1986) S.18-23: Blair, D.C., M.E. Maron: Full-text information retrieval ... Inf. proc. man. 26(1990) S.437-447.
  15. Biebricher, P.; Fuhr, N.; Niewelt, B.: ¬Der AIR-Retrievaltest (1986) 0.02 
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    Source
    Automatische Indexierung zwischen Forschung und Anwendung, Hrsg.: G. Lustig
  16. Hull, D.; Grefenstette, G.; Schulze, B.M.; Gaussier, E.; Schütze, H.; Pedersen, J.: Xerox TREC-5 site reports : routing, filtering, NLP, and Spanisch tracks (1997) 0.02 
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  17. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.02 
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    Abstract
    Retrievaltests sind die anerkannteste Methode, um neue Verfahren der Inhaltserschließung gegenüber traditionellen Verfahren zu rechtfertigen. Im Rahmen einer Diplomarbeit wurden zwei grundsätzlich unterschiedliche Systeme der automatischen inhaltlichen Erschließung anhand der Pressedatenbank des Verlagshauses Gruner + Jahr (G+J) getestet und evaluiert. Untersucht wurde dabei natürlichsprachliches Retrieval im Vergleich zu Booleschem Retrieval. Bei den beiden Systemen handelt es sich zum einen um Autonomy von Autonomy Inc. und DocCat, das von IBM an die Datenbankstruktur der G+J Pressedatenbank angepasst wurde. Ersteres ist ein auf natürlichsprachlichem Retrieval basierendes, probabilistisches System. DocCat demgegenüber basiert auf Booleschem Retrieval und ist ein lernendes System, das aufgrund einer intellektuell erstellten Trainingsvorlage indexiert. Methodisch geht die Evaluation vom realen Anwendungskontext der Textdokumentation von G+J aus. Die Tests werden sowohl unter statistischen wie auch qualitativen Gesichtspunkten bewertet. Ein Ergebnis der Tests ist, dass DocCat einige Mängel gegenüber der intellektuellen Inhaltserschließung aufweist, die noch behoben werden müssen, während das natürlichsprachliche Retrieval von Autonomy in diesem Rahmen und für die speziellen Anforderungen der G+J Textdokumentation so nicht einsetzbar ist
  18. Kazai, G.; Lalmas, M.: ¬The overlap problem in content-oriented XML retrieval evaluation (2004) 0.02 
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  19. 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
  20. 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

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