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  1. Information retrieval experiment (1981) 0.02
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    Content
    Enthält die Beiträge: ROBERTSON, S.E.: The methodology of information retrieval experiment; RIJSBERGEN, C.J. van: Retrieval effectiveness; BELKIN, N.: Ineffable concepts in information retrieval; TAGUE, J.M.: The pragmatics of information retrieval experimentation; LANCASTER, F.W.: Evaluation within the environment of an operating information service; BARRACLOUGH, E.D.: Opportunities for testing with online systems; KEEN, M.E.: Laboratory tests of manual systems; ODDY, R.N.: Laboratory tests: automatic systems; HEINE, M.D.: Simulation, and simulation experiments; COOPER, W.S.: Gedanken experimentation: an alternative to traditional system testing?; SPARCK JONES, K.: Actual tests - retrieval system tests; EVANS, L.: An experiment: search strategy variation in SDI profiles; SALTON, G.: The Smart environment for retrieval system evaluation - advantage and problem areas
  2. ¬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
  3. 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
  4. TREC: experiment and evaluation in information retrieval (2005) 0.01
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    Abstract
    The Text REtrieval Conference (TREC), a yearly workshop hosted by the US government's National Institute of Standards and Technology, provides the infrastructure necessary for large-scale evaluation of text retrieval methodologies. With the goal of accelerating research in this area, TREC created the first large test collections of full-text documents and standardized retrieval evaluation. The impact has been significant; since TREC's beginning in 1992, retrieval effectiveness has approximately doubled. TREC has built a variety of large test collections, including collections for such specialized retrieval tasks as cross-language retrieval and retrieval of speech. Moreover, TREC has accelerated the transfer of research ideas into commercial systems, as demonstrated in the number of retrieval techniques developed in TREC that are now used in Web search engines. This book provides a comprehensive review of TREC research, summarizing the variety of TREC results, documenting the best practices in experimental information retrieval, and suggesting areas for further research. The first part of the book describes TREC's history, test collections, and retrieval methodology. Next, the book provides "track" reports -- describing the evaluations of specific tasks, including routing and filtering, interactive retrieval, and retrieving noisy text. The final part of the book offers perspectives on TREC from such participants as Microsoft Research, University of Massachusetts, Cornell University, University of Waterloo, City University of New York, and IBM. The book will be of interest to researchers in information retrieval and related technologies, including natural language processing.
    LCSH
    Information storage and retrieval systems / Congresses
    Subject
    Information storage and retrieval systems / Congresses
  5. Cross-language information retrieval (1998) 0.00
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    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."