Search (8 results, page 1 of 1)

  • × author_ss:"Sparck Jones, K."
  • × year_i:[1990 TO 2000}
  1. Sparck Jones, K.: ¬The role of artificial intelligence in information retrieval (1991) 0.01 
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    Abstract
    Presents a view of the scope of artificial intelligence (AI) in information retrieval (IR). Considers potential roles of AI and IR, evaluating AI from a realistic point od view and within a wide information management potential, not just because AI is itself insufficiently developed, but because many information management tasks are properly shallow information processing ones. There is nevertheless an important place for specific applications of AI or AI-derived technology when particular constraints can be placed on the information management tasks involved
    Source
    Journal of the American Society for Information Science. 42(1991) no.8, S.558-565
  2. Lewis, D.D.; Sparck Jones, K.: Natural language processing for information retrieval (1996) 0.00 
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  3. Sparck Jones, K.: Reflections on TREC : TREC-2 (1995) 0.00 
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    Abstract
    Discusses the TREC programme as a major enterprise in information retrieval research. It reviews its structure as an evaluation exercise, characterises the methods of indexing and retrieval being tested within it in terms of the approaches to system performance factors these represent; analyses the test results for solid, overall conclusions that can be drawn from them; and, in the light of the particular features of the test data, assesses TREC both for generally applicable findings that emerge from it and for directions it offers for future research
    Source
    Information processing and management. 31(1995) no.3, S.291-314
  4. Lewis, D.D.; Sparck Jones, K.: Natural language processing for information retrieval (1997) 0.00 
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    Imprint
    The Hague : International Federation for Information and Documentation (FID)
  5. Sparck Jones, K.: Reflections on TREC (1997) 0.00 
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    Abstract
    This paper discusses the Text REtrieval Conferences (TREC) programme as a major enterprise in information retrieval research. It reviews its structure as an evaluation exercise, characterises the methods of indexing and retrieval being tested within its terms of the approaches to system performance factors these represent; analyses the test results for solid, overall conclusions that can be drawn from them; and, in the light of the particular features of the test data, assesses TREC both for generally applicable findings that emerge from it and for directions it offers for future research
    Footnote
    Wiederabdruck aus: Information processing and management 31(1995) no.3, S.192-314
    Imprint
    The Hague : International Federation for Information and Documentation (FID)
  6. Sparck Jones, K.; Endres-Niggemeyer, B.: Introduction: automatic summarizing (1995) 0.00 
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    Source
    Information processing and management. 31(1995) no.5, S.625-630
  7. Robertson, S.E.; Sparck Jones, K.: Simple, proven approaches to text retrieval (1997) 0.00 
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    Abstract
    This technical note describes straightforward techniques for document indexing and retrieval that have been solidly established through extensive testing and are easy to apply. They are useful for many different types of text material, are viable for very large files, and have the advantage that they do not require special skills or training for searching, but are easy for end users. The document and text retrieval methods described here have a sound theoretical basis, are well established by extensive testing, and the ideas involved are now implemented in some commercial retrieval systems. Testing in the last few years has, in particular, shown that the methods presented here work very well with full texts, not only title and abstracts, and with large files of texts containing three quarters of a million documents. These tests, the TREC Tests (see Harman 1993 - 1997; IP&M 1995), have been rigorous comparative evaluations involving many different approaches to information retrieval. These techniques depend an the use of simple terms for indexing both request and document texts; an term weighting exploiting statistical information about term occurrences; an scoring for request-document matching, using these weights, to obtain a ranked search output; and an relevance feedback to modify request weights or term sets in iterative searching. The normal implementation is via an inverted file organisation using a term list with linked document identifiers, plus counting data, and pointers to the actual texts. The user's request can be a word list, phrases, sentences or extended text.
  8. Sparck Jones, K.; Jones, G.J.F.; Foote, J.T.; Young, S.J.: Experiments in spoken document retrieval (1996) 0.00 
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    Source
    Information processing and management. 32(1996) no.4, S.399-417

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