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  • × author_ss:"Salton, G."
  1. Salton, G.; Buckley, C.; Smith, M.: On the application of syntactic methodologies in automatic text analysis (1990) 0.01
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    Source
    Information processing and management. 26(1990) no.1, S.73-92
    Year
    1990
  2. Salton, G.: Future prospects for text-based information retrieval (1990) 0.00
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    Year
    1990
  3. Salton, G.; Araya, J.: On the use of clustered file organizations in information search and retrieval (1990) 0.00
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    Year
    1990
  4. Salton, G.; Buckley, C.: Improving retrieval performance by relevance feedback (1990) 0.00
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    Source
    Journal of the American Society for Information Science. 41(1990) no.4, S.288-297
    Year
    1990
  5. Salton, G.: ¬The Smart environment for retrieval systeme valuation : advantages and problem areas (1981) 0.00
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  6. Salton, G.: Another look at automatic text-retrieval systems (1986) 0.00
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    Footnote
    Bezugnahme auf: Blair, D.C.: An evaluation of retrieval effectiveness for a full-text document-retrieval system. Comm. ACM 28(1985) S.280-299. - Vgl. auch: Blair, D.C.: Full text retrieval ... Int. Class. 13(1986) S.18-23; Blair, D.C., M.E. Maron: full-text information retrieval ... Inf. Proc. Man. 26(1990) S.437-447.
  7. Salton, G.; Buckley, C.: Approaches to global text analysis (1990) 0.00
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    Year
    1990
  8. Salton, G.: Automatic processing of foreign language documents (1985) 0.00
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    Abstract
    The attempt to computerize a process, such as indexing, abstracting, classifying, or retrieving information, begins with an analysis of the process into its intellectual and nonintellectual components. That part of the process which is amenable to computerization is mechanical or algorithmic. What is not is intellectual or creative and requires human intervention. Gerard Salton has been an innovator, experimenter, and promoter in the area of mechanized information systems since the early 1960s. He has been particularly ingenious at analyzing the process of information retrieval into its algorithmic components. He received a doctorate in applied mathematics from Harvard University before moving to the computer science department at Cornell, where he developed a prototype automatic retrieval system called SMART. Working with this system he and his students contributed for over a decade to our theoretical understanding of the retrieval process. On a more practical level, they have contributed design criteria for operating retrieval systems. The following selection presents one of the early descriptions of the SMART system; it is valuable as it shows the direction automatic retrieval methods were to take beyond simple word-matching techniques. These include various word normalization techniques to improve recall, for instance, the separation of words into stems and affixes; the correlation and clustering, using statistical association measures, of related terms; and the identification, using a concept thesaurus, of synonymous, broader, narrower, and sibling terms. They include, as weIl, techniques, both linguistic and statistical, to deal with the thorny problem of how to automatically extract from texts index terms that consist of more than one word. They include weighting techniques and various documentrequest matching algorithms. Significant among the latter are those which produce a retrieval output of citations ranked in relevante order. During the 1970s, Salton and his students went an to further refine these various techniques, particularly the weighting and statistical association measures. Many of their early innovations seem commonplace today. Some of their later techniques are still ahead of their time and await technological developments for implementation. The particular focus of the selection that follows is an the evaluation of a particular component of the SMART system, a multilingual thesaurus. By mapping English language expressions and their German equivalents to a common concept number, the thesaurus permitted the automatic processing of German language documents against English language queries and vice versa. The results of the evaluation, as it turned out, were somewhat inconclusive. However, this SMART experiment suggested in a bold and optimistic way how one might proceed to answer such complex questions as What is meant by retrieval language compatability? How it is to be achieved, and how evaluated?