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Sparck Jones, K.; Kay, M.: Linguistik und Informationswissenschaft (1976)
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- Abstract
- Diese Arbeit befaßt sich mit den sprachlichen Aspekten der Informationswissenschaft, insbesondere mit den sprachlichen Komponenten der Analyse, der beschreibung und dem Retrieval von Dokumenten. Dabei wird erforscht, welche linguistischen Verfahren und Theorien von der Informationswissenschaft genützt werden können. Unter anderem werden untersucht die Anwendung der Sprachtheorie auf die Struktur der Erkenntnis, die Verwertung der Phonologie, Morphologie, Syntax und Semantik in der Organisation, der Speicherung und in der Überbringung von Informationen
- Issue
- Aus dem Englischen übersetzt von E. Couper u. R. Kuhlen.
-
Sparck Jones, K.: Metareflections on TREC (2005)
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- Date
- 29. 3.1996 18:16:49
27. 5.2007 20:08:43
- Language
- e
-
Needham, R.M.; Sparck Jones, K.: Keywords and clumps (1985)
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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.
- Footnote
- Original in: Journal of documentation 20(1964) no.1, S.5-15.
- Language
- e
-
Sparck Jones, K.: Summary performance comparisons TREC-2 through TREC-8 (2001)
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- Date
- 26. 3.2002 20:16:20
- Language
- e
-
Sparck Jones, K.: Revisiting classification for retrieval (2005)
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- Date
- 10. 3.1997 20:31:13
- Language
- e
- Theme
- Klassifikationssysteme im Online-Retrieval
-
Sparck Jones, K.: Retrieval system tests 1958-1978 (1981)
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- Date
- 30.11.1995 20:37:26
- Language
- e
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Sparck Jones, K.: ¬The Cranfield tests (1981)
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- Date
- 30.11.1995 20:37:26
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-
Sparck Jones, K.: Some thoughts on classification for retrieval (2005)
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- Date
- 10. 3.1997 20:31:13
- Language
- e
- Theme
- Klassifikationssysteme im Online-Retrieval
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Sparck Jones, K.: Search term relevance weighting given little relevance information (1979)
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- Date
- 15. 8.1998 20:00:41
- Language
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Strzalkowski, T.; Sparck Jones, K.: NLP track at TREC-5 (1997)
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- Date
- 27. 2.1999 20:44:43
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- e
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Sparck Jones, K.; Walker, S.; Robertson, S.E.: ¬A probabilistic model of information retrieval : development and comparative experiments - part 1 (2000)
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- Date
- 27.12.2007 19:27:29
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Sparck Jones, K.: IDF term weighting and IR research lessons (2004)
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- 10. 3.1997 20:31:13
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Sparck Jones, K.: ¬A statistical interpretation of term specificity and its application in retrieval (2004)
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Sparck Jones, K.: Some thoughts on classification for retrieval (1970)
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- Theme
- Klassifikationssysteme im Online-Retrieval
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Sparck Jones, K.: Automatic keyword classification for information retrieval (1971)
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Sparck Jones, K.: Automatic classification (1976)
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Sparck Jones, K.; Tait, J.I.: Automatic search term variant generation (1984)
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Sparck Jones, K.; Jackson, D.M.: ¬The use of automatically obtained keyword classification for information retrieval (1970)
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Sparck Jones, K.: ¬A statistical interpretation of term specifity and its application in retrieval (1972)
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Sparck Jones, K.: Index term weighting (1973)
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