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  • × theme_ss:"Computerlinguistik"
  1. Sparck Jones, K.; Kay, M.: Linguistik und Informationswissenschaft (1976) 0.15
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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
  2. Kay, M.; Sparck Jones, K.: Automated language processing (1971) 0.12
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  3. Lewis, D.D.; Sparck Jones, K.: Natural language processing for information retrieval (1996) 0.10
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  4. Jones, K.: Linguistic searching versus relevance ranking : DR-LINK and TARGET (1999) 0.10
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  5. McCune, B.P.; Tong, R.M.; Dean, J.S.: Rubric: a system for rule-based information retrieval (1985) 0.09
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.440-445.
  6. Porter, M.F.: ¬An algorithm for suffix stripping (1980) 0.09
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.313-316.
  7. Franke-Maier, M.: Computerlinguistik und Bibliotheken : Editorial (2016) 0.07
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    Abstract
    Vor 50 Jahren, im Februar 1966, wies Floyd M. Cammack auf den Zusammenhang von "Linguistics and Libraries" hin. Er ging dabei von dem Eintrag für "Linguistics" in den Library of Congress Subject Headings (LCSH) von 1957 aus, der als Verweis "See Language and Languages; Philology; Philology, Comparative" enthielt. Acht Jahre später kamen unter dem Schlagwort "Language and Languages" Ergänzungen wie "language data processing", "automatic indexing", "machine translation" und "psycholinguistics" hinzu. Für Cammack zeigt sich hier ein Netz komplexer Wechselbeziehungen, die unter dem Begriff "Linguistics" zusammengefasst werden sollten. Dieses System habe wichtigen Einfluss auf alle, die mit dem Sammeln, Organisieren, Speichern und Wiederauffinden von Informationen befasst seien. (Cammack 1966:73). Hier liegt - im übertragenen Sinne - ein Heft vor Ihnen, in dem es um computerlinguistische Verfahren in Bibliotheken geht. Letztlich geht es um eine Versachlichung der Diskussion, um den Stellenwert der Inhaltserschliessung und die Rekalibrierung ihrer Wertschätzung in Zeiten von Mega-Indizes und Big Data. Der derzeitige Widerspruch zwischen dem Wunsch nach relevanter Treffermenge in Rechercheoberflächen vs. der Erfahrung des Relevanz-Rankings ist zu lösen. Explizit auch die Frage, wie oft wir von letzterem enttäuscht wurden und was zu tun ist, um das Verhältnis von recall und precision wieder in ein angebrachtes Gleichgewicht zu bringen. Unsere Nutzerinnen und Nutzer werden es uns danken.
    Content
    Editorial zu einem Themenschwerpunkt 'Computerlinguistik und Bibliotheken'. Vgl-: http://0277.ch/ojs/index.php/cdrs_0277/article/view/159/349.
  8. Sparck Jones, K.: Synonymy and semantic classification (1986) 0.07
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  9. Tenopir, C.; Cahn, P.: TARGET & FREESTYLE : DIALOG and Mead join the relevance ranks (1994) 0.07
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.446-456.
  10. Zhang, H.J.; Low, C.Y.; Smoliar, S.W.; Lu. J.H.: Video parsing, retrieval and browsing : an integrated and content-based solution (1995) 0.07
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.503-512
  11. Strzalkowski, T.: Robust text processing in automated information retrieval (1994) 0.07
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.317-322.
  12. Hayes, P.J.; Knecht, L.E.; Cellio, M.J.: ¬A news story categorization system (1988) 0.07
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.518-526
  13. Rau, L.F.: Conceptual information extraction and retrieval from natural language input (198) 0.07
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.527-533
  14. Robertson, S.E.; Sparck Jones, K.: Relevance weighting of search terms (1976) 0.06
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  15. Lewis, D.D.; Sparck Jones, K.: Natural language processing for information retrieval (1997) 0.06
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  16. Pritchard-Schoch, T.: Natural language comes of age (1993) 0.06
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    Abstract
    Discusses natural languages and the natural language implementations of Westlaw's full-text legal documents, Westlaw Is Natural. Natural language is not aritificial intelligence but a hybrid of linguistics, mathematics and statistics. Provides 3 classes of retrieval models. Explains how Westlaw processes an English query. Assesses WIN. Covers WIN enhancements; the natural language features of Congressional Quarterly's Washington Alert using a document for a query; the personal librarian front end search software and Dowquest from Dow Jones news/retrieval. Conmsiders whether natural language encourages fuzzy thinking and whether Boolean logic will still be needed
  17. Jones, D.: Analogical natural language processing (1996) 0.06
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  18. Needham, R.M.; Sparck Jones, K.: Keywords and clumps (1985) 0.06
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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.
  19. Grefenstette, G.: Explorations in automatic thesaurus discovery (1994) 0.05
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    Footnote
    Rez. in: Journal of documentation 51(1995) no.4, S.447-448 (K. Sparck Jones)
  20. Sparck Jones, K.; Galliers, J.R.: Evaluating natural language processing systems : an analysis and review (1996) 0.04
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Years

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  • ru 1
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  • m 44
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  • x 9
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