Search (9 results, page 1 of 1)

  • × author_ss:"Sparck Jones, K."
  • × year_i:[1970 TO 1980}
  1. Sparck Jones, K.: Automatic classification (1976) 0.00 
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    Source
    Classification in the 1970s: a second look. Rev. ed. Ed.: A. Maltby
    Type
    a
  2. Sparck Jones, K.: ¬A statistical interpretation of term specifity and its application in retrieval (1972) 0.00 
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  3. Sparck Jones, K.; Jackson, D.M.: ¬The use of automatically obtained keyword classification for information retrieval (1970) 0.00 
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  4. Sparck Jones, K.: Index term weighting (1973) 0.00 
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    Type
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  5. Robertson, S.E.; Sparck Jones, K.: Relevance weighting of search terms (1976) 0.00 
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    Abstract
    Examines statistical techniques for exploiting relevance information to weight search terms. These techniques are presented as a natural extension of weighting methods using information about the distribution of index terms in documents in general. A series of relevance weighting functions is derived and is justified by theoretical considerations. In particular, it is shown that specific weighted search methods are implied by a general probabilistic theory of retrieval. Different applications of relevance weighting are illustrated by experimental results for test collections
    Type
    a
  6. Kay, M.; Sparck Jones, K.: Automated language processing (1971) 0.00 
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  7. Sparck Jones, K.: Some thoughts on classification for retrieval (1970) 0.00 
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    Abstract
    The suggestion that classifications for retrieval should be constructed automatically raises some serious problems concerning the sorts of classification which are required, and the way in which formal classification theories should be exploited, given that a retrieval classification is required for a purpose. These difficulties have not been sufficiently considered, and the paper therefore attempts an analysis of them, though no solution of immediate application can be suggested. Starting with the illustrative proposition that a polythetic, multiple, unordered classification is required in automatic thesaurus construction, this is considered in the context of classification in general, where eight sorts of classification can be distinguished, each covering a range of class definitions and class-finding algorithms. The problem which follows is that since there is generally no natural or best classification of a set of objects as such, the evaluation of alternative classifications requires either formal criteria of goodness of fit, or, if a classification is required for a purpose, a precises statement of that purpose. In any case a substantive theory of classification is needed, which does not exist; and since sufficiently precise specifications of retrieval requirements are also lacking, the only currently available approach to automatic classification experiments for information retrieval is to do enough of them
    Type
    a
  8. Sparck Jones, K.; Rijsbergen, C.J. van: Progress in documentation : Information retrieval test collection (1976) 0.00 
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    Abstract
    Many retrieval experiments have been based on inadequate test collections, and current research is hampered by the lack of proper collections. This short review does not attempt a fully docuemted survey of all the collections used in the past decade: hopefully representative examples have been studied to throw light on the requriements test collections should meet, to show how past collections have been defective, and to suggest guidelines for a future "ideal" test collection. This specifications for this collection can be taken as an indirect comment on our present state of knowledge of major retrieval system variables, and experience in conducting experiments.
    Type
    a
  9. Sparck Jones, K.: Search term relevance weighting given little relevance information (1979) 0.00 
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