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  • × author_ss:"Sparck Jones, K."
  1. Kay, M.; Sparck Jones, K.: Automated language processing (1971) 0.07
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    Source
    Annual review of information science and technology. 6(1971), S.141-166
  2. Sparck Jones, K.; Walker, S.; Robertson, S.E.: ¬A probabilistic model of information retrieval : development and comparative experiments - part 1 (2000) 0.06
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    Date
    27.12.2007 19:27:29
    Source
    Information processing and management. 36(2000) no.6, S.779-808
  3. Sparck Jones, K.: ¬The role of artificial intelligence in information retrieval (1991) 0.04
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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
  4. Lewis, D.D.; Sparck Jones, K.: Natural language processing for information retrieval (1996) 0.03
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  5. Sparck Jones, K.; Walker, S.; Robertson, S.E.: ¬A probabilistic model of information retrieval : development and comparative experiments - part 2 (2000) 0.02
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    Source
    Information processing and management. 36(2000) no.6, S.809-840
  6. Sparck Jones, K.: Reflections on TREC : TREC-2 (1995) 0.02
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    Source
    Information processing and management. 31(1995) no.3, S.291-314
  7. Sparck Jones, K.; Endres-Niggemeyer, B.: Introduction: automatic summarizing (1995) 0.02
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    Source
    Information processing and management. 31(1995) no.5, S.625-630
  8. Lewis, D.D.; Sparck Jones, K.: Natural language processing for information retrieval (1997) 0.02
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  9. Needham, R.M.; Sparck Jones, K.: Keywords and clumps (1985) 0.02
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    Abstract
    The selection that follows was chosen as it represents "a very early paper an the possibilities allowed by computers an documentation." In the early 1960s computers were being used to provide simple automatic indexing systems wherein keywords were extracted from documents. The problem with such systems was that they lacked vocabulary control, thus documents related in subject matter were not always collocated in retrieval. To improve retrieval by improving recall is the raison d'être of vocabulary control tools such as classifications and thesauri. The question arose whether it was possible by automatic means to construct classes of terms, which when substituted, one for another, could be used to improve retrieval performance? One of the first theoretical approaches to this question was initiated by R. M. Needham and Karen Sparck Jones at the Cambridge Language Research Institute in England.t The question was later pursued using experimental methodologies by Sparck Jones, who, as a Senior Research Associate in the Computer Laboratory at the University of Cambridge, has devoted her life's work to research in information retrieval and automatic naturai language processing. Based an the principles of numerical taxonomy, automatic classification techniques start from the premise that two objects are similar to the degree that they share attributes in common. When these two objects are keywords, their similarity is measured in terms of the number of documents they index in common. Step 1 in automatic classification is to compute mathematically the degree to which two terms are similar. Step 2 is to group together those terms that are "most similar" to each other, forming equivalence classes of intersubstitutable terms. The technique for forming such classes varies and is the factor that characteristically distinguishes different approaches to automatic classification. The technique used by Needham and Sparck Jones, that of clumping, is described in the selection that follows. Questions that must be asked are whether the use of automatically generated classes really does improve retrieval performance and whether there is a true eco nomic advantage in substituting mechanical for manual labor. Several years after her work with clumping, Sparck Jones was to observe that while it was not wholly satisfactory in itself, it was valuable in that it stimulated research into automatic classification. To this it might be added that it was valuable in that it introduced to libraryl information science the methods of numerical taxonomy, thus stimulating us to think again about the fundamental nature and purpose of classification. In this connection it might be useful to review how automatically derived classes differ from those of manually constructed classifications: 1) the manner of their derivation is purely a posteriori, the ultimate operationalization of the principle of literary warrant; 2) the relationship between members forming such classes is essentially statistical; the members of a given class are similar to each other not because they possess the class-defining characteristic but by virtue of sharing a family resemblance; and finally, 3) automatically derived classes are not related meaningfully one to another, that is, they are not ordered in traditional hierarchical and precedence relationships.
  10. Sparck Jones, K.: Fashionable trends and feasible strategies in information management (1988) 0.01
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    Source
    Information processing and management. 24(1988), S.703-711
  11. Sparck Jones, K.; Jones, G.J.F.; Foote, J.T.; Young, S.J.: Experiments in spoken document retrieval (1996) 0.01
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    Source
    Information processing and management. 32(1996) no.4, S.399-417
  12. Sparck Jones, K.: Reflections on TREC (1997) 0.01
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    Footnote
    Wiederabdruck aus: Information processing and management 31(1995) no.3, S.192-314
  13. Sparck Jones, K.; Galliers, J.R.: Evaluating natural language processing systems : an analysis and review (1996) 0.01
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  14. Sparck Jones, K.: Automatic summarising : the state of the art (2007) 0.01
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    Source
    Information processing and management. 43(2007) no.6, S.1449-1481
  15. Sparck Jones, K.: Metareflections on TREC (2005) 0.01
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    Date
    29. 3.1996 18:16:49
  16. Robertson, S.E.; Sparck Jones, K.: Relevance weighting of search terms (1976) 0.00
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    Source
    Journal of the American Society for Information Science. 27(1976), S.129-146