Search (46 results, page 2 of 3)

  • × theme_ss:"Automatisches Indexieren"
  • × year_i:[1980 TO 1990}
  1. Lustig, G.: Weiterentwicklung der automatischen Indexierung im Projekt AIR (1984) 0.00
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  2. Hüther, H.: Zur Aufwandsabschätzung beim Aufbau eines automatischen Indexierungssystems (1985) 0.00
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  3. Advances in intelligent retrieval: Proc. of a conference ... Wadham College, Oxford, 16.-17.4.1985 (1986) 0.00
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    Content
    Enthält die Beiträge: ADDIS, T.: Extended relational analysis: a design approach to knowledge-based systems; PARKINSON, D.: Supercomputers and non-numeric processing; McGREGOR, D.R. u. J.R. MALONE: An architectural approach to advances in information retrieval; ALLEN, M.J. u. O.S. HARRISON: Word processing and information retrieval: some practical problems; MURTAGH, F.: Clustering and nearest neighborhood searching; ENSER, P.G.B.: Experimenting with the automatic classification of books; TESKEY, N. u. Z. RAZAK: An analysis of ranking for free text retrieval systems; ZARRI, G.P.: Interactive information retrieval: an artificial intelligence approach to deal with biographical data; HANCOX, P. u. F. SMITH: A case system processor for the PRECIS indexing language; ROUAULT, J.: Linguistic methods in information retrieval systems; ARAGON-RAMIREZ, V. u. C.D. PAICE: Design of a system for the online elucidation of natural language search statements; BROOKS, H.M., P.J. DANIELS u. N.J. BELKIN: Problem descriptions and user models: developing an intelligent interface for document retrieval systems; BLACK, W.J., P. HARGREAVES u. P.B. MAYES: HEADS: a cataloguing advisory system; BELL, D.A.: An architecture for integrating data, knowledge, and information bases
  4. Gräbnitz, V.: PASSAT: Programm zur automatischen Selektion von Stichwörtern aus Texten (1987) 0.00
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  5. Werner, H.: Indexierung auf linguistischer Grundlage am Beispiel von JUDO-DS(1) (1982) 0.00
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  6. Lück, W.: Erfahrungen mit dem automatischen Indexierungssystem AIR/PHYS (1988) 0.00
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  7. Schwantner, M.: Entwicklung und Pflege des Indexierungswörterbuches PHYS/PILOT (1988) 0.00
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  8. Schneider, C.; Womser-Hacker, C.: Inhaltserschließungssysteme für Patenttexte : Test und Systemvergleich im Projekt PADOK (1986) 0.00
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  9. Porter, M.F.: ¬An algorithm for suffix stripping (1980) 0.00
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  10. Fagan, J.L.: ¬The effectiveness of a nonsyntactic approach to automatic phrase indexing for document retrieval (1989) 0.00
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    Abstract
    It may be possible to improve the quality of automatic indexing systems by using complex descriptors, for example, phrases, in addition to the simple descriptors (words or word stems) that are normally used in automatically constructed representations of document content. This study is directed toward the goal of developing effective methods of identifying phrases in natural language text from which good quality phrase descriptors can be constructed. The effectiveness of one method, a simple nonsyntactic phrase indexing procedure, has been tested on five experimental document collections. The results have been analyzed in order to identify the inadequacies of the procedure, and to determine what kinds of information about text structure are needed in order to construct phrase descriptors that are good indicators of document content. Two primary conclusions have been reached: (1) In the retrieval experiments, the nonsyntactic phrase construction procedure did not consistently yield substantial improvements in effectiveness. It is therefore not likely that phrase indexing of this kind will prove to be an important method of enhancing the performance of automatic document indexing and retrieval systems in operational environments. (2) Many of the shortcomings of the nonsyntactic approach can be overcome by incorporating syntactic information into the phrase construction process. However, a general syntactic analysis facility may be required, since many useful sources of phrases cannot be exploited if only a limited inventory of syntactic patterns can be recognized. Further research should be conducted into methods of incorporating automatic syntactic analysis into content analysis for document retrieval.
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  11. Vledutz-Stokolov, N.: Concept recognition in an automatic text-processing system for the life sciences (1987) 0.00
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    Abstract
    This article describes a natural-language text-processing system designed as an automatic aid to subject indexing at BIOSIS. The intellectual procedure the system should model is a deep indexing with a controlled vocabulary of biological concepts - Concept Headings (CHs). On the average, ten CHs are assigned to each article by BIOSIS indexers. The automatic procedure consists of two stages: (1) translation of natural-language biological titles into title-semantic representations which are in the constructed formalized language of Concept Primitives, and (2) translation of the latter representations into the language of CHs. The first stage is performed by matching the titles agianst the system's Semantic Vocabulary (SV). The SV currently contains approximately 15.000 biological natural-language terms and their translations in the language of Concept Primitives. Tor the ambiguous terms, the SV contains the algorithmical rules of term disambiguation, ruels based on semantic analysis of the contexts. The second stage of the automatic procedure is performed by matching the title representations against the CH definitions, formulated as Boolean search strategies in the language of Concept Primitives. Three experiments performed with the system and their results are decribed. The most typical problems the system encounters, the problems of lexical and situational ambiguities, are discussed. The disambiguation techniques employed are described and demonstrated in many examples
    Type
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  12. Thönssen, B.: Automatische Indexierung und Schnittstellen zu Thesauri (1988) 0.00
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  13. Biebricher, P.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬Das automatische Indexierungssystem AIR/PHYS (1988) 0.00
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  14. Biebricher, P.; Fuhr, N.; Niewelt, B.: ¬Der AIR-Retrievaltest (1986) 0.00
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  15. Olsgaard, J.N.; Evans, E.J.: Improving keyword indexing (1981) 0.00
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  16. Stock, M.: Textwortmethode und Übersetzungsrelation : Eine Methode zum Aufbau von kombinierten Literaturnachweis- und Terminologiedatenbanken (1989) 0.00
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  17. Croft, W.B.: Automatic indexing : file organization and display for information retrieval (1989) 0.00
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  18. Needham, R.M.; Sparck Jones, K.: Keywords and clumps (1985) 0.00
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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.
    Source
    Theory of subject analysis: a sourcebook. Ed.: L.M. Chan, et al
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  19. Zimmermann, H.: Automatische Indexierung: Entwicklung und Perspektiven (1983) 0.00
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  20. Biebricher, P.; Fuhr, N.; Knorz, G.; Lustig, G.; Schwandtner, M.: Entwicklung und Anwendung des automatischen Indexierungssystems AIR/PHYS (1988) 0.00
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