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  • × author_ss:"Sparck Jones, K."
  1. Sparck Jones, K.; Walker, S.; Robertson, S.E.: ¬A probabilistic model of information retrieval : development and comparative experiments - part 1 (2000) 0.00
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  2. Sparck Jones, K.; Walker, S.; Robertson, S.E.: ¬A probabilistic model of information retrieval : development and comparative experiments - part 2 (2000) 0.00
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  3. Sparck Jones, K.: Search term relevance weighting given little relevance information (1979) 0.00
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    Source
    Journal of documentation. 35(1979), S.30-48
  4. Strzalkowski, T.; Sparck Jones, K.: NLP track at TREC-5 (1997) 0.00
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    Imprint
    Gaithersburgh, MD : National Institute of Standards and Technology
  5. Sparck Jones, K.; Endres-Niggemeyer, B.: Introduction: automatic summarizing (1995) 0.00
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    Abstract
    Automatic summarizing is a research topic whose time has come. The papers illustrate some of the relevant work already under way. Places these papers in their wider context: why research and development on automatic summarizing is timely, what areas of work and ideas it should draw on, how future investigations and experiments can be effectively framed
  6. Lewis, D.D.; Sparck Jones, K.: Natural language processing for information retrieval (1997) 0.00
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    Footnote
    Wiederabdruck aus: Communications of the ACM 39(1996) no.1, S.92-101
    Source
    From classification to 'knowledge organization': Dorking revisited or 'past is prelude'. A collection of reprints to commemorate the firty year span between the Dorking Conference (First International Study Conference on Classification Research 1957) and the Sixth International Study Conference on Classification Research (London 1997). Ed.: A. Gilchrist
  7. Sparck Jones, K.: Automatic summarising : the state of the art (2007) 0.00
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    Abstract
    This paper reviews research on automatic summarising in the last decade. This work has grown, stimulated by technology and by evaluation programmes. The paper uses several frameworks to organise the review, for summarising itself, for the factors affecting summarising, for systems, and for evaluation. The review examines the evaluation strategies applied to summarising, the issues they raise, and the major programmes. It considers the input, purpose and output factors investigated in recent summarising research, and discusses the classes of strategy, extractive and non-extractive, that have been explored, illustrating the range of systems built. The conclusions drawn are that automatic summarisation has made valuable progress, with useful applications, better evaluation, and more task understanding. But summarising systems are still poorly motivated in relation to the factors affecting them, and evaluation needs taking much further to engage with the purposes summaries are intended to serve and the contexts in which they are used.
  8. Sparck Jones, K.: Revisiting classification for retrieval (2005) 0.00
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    Abstract
    Purpose - This short note seeks to respond to Hjørland and Pederson's paper "A substantive theory of classification for information retrieval" which starts from Sparck Jones's, "Some thoughts on classification for retrieval", originally published in 1970. Design/methodology/approach - The note comments on the context in which the 1970 paper was written, and on Hjørland and Pedersen's views, emphasising the need for well-grounded classification theory and application. Findings - The note maintains that text-based, a posteriori, classification, as increasingly found in applications, is likely to be more useful, in general, than a priori classification. Originality/value - The note elaborates on points made in a well-received earlier paper.
    Source
    Journal of documentation. 61(2005) no.5, S.598-601