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  • × theme_ss:"Automatisches Indexieren"
  1. Stock, W.G.: Textwortmethode : Norbert Henrichs zum 65. (3) (2000) 0.10 
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    Abstract
    Nur wenige Dokumentationsmethoden werden mit dem Namen ihrer Entwickler assoziiert. Ausnahmen sind Melvil Dewey (DDC), S.R. Ranganathan (Colon Classification) - und Norbert Henrichs. Seine Textwortmethode ermöglicht die Indexierung und das Retrieval von Literatur aus Fachgebieten, die keine allseits akzeptierte Fachterminologie vorweisen, also viele Sozial- und Geisteswissenschaften, vorneweg die Philosophie. Für den Einsatz in der elektronischen Philosophie-Dokumentation hat Henrichs in den späten sechziger Jahren die Textwortmethode entworfen. Er ist damit nicht nur einer der Pioniere der Anwendung der elektronischen Datenverarbeitung in der Informationspraxis, sondern auch der Pionier bei der Dokumentation terminologisch nicht starrer Fachsprachen
    Type
    a
  2. Lepsky, K.: Automatisierung in der Sacherschließung : Maschinelles Indexieren von Titeldaten (1996) 0.06 
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    Series
    Zeitschrift für Bibliothekswesen und Bibliographie: Sonderh.63
    Type
    a
  3. Bloomfield, M.: Indexing : neglected and poorly understood (2001) 0.03 
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    Abstract
    The growth of the Internet has highlighted the use of machine indexing. The difficulties in using the Internet as a searching device can be frustrating. The use of the term "Python" is given as an example. Machine indexing is noted as "rotten" and human indexing as "capricious." The problem seems to be a lack of a theoretical foundation for the art of indexing. What librarians have learned over the last hundred years has yet to yield a consistent approach to what really works best in preparing index terms and in the ability of our customers to search the various indexes. An attempt is made to consider the elements of indexing, their pros and cons. The argument is made that machine indexing is far too prolific in its production of index terms. Neither librarians nor computer programmers have made much progress to improve Internet indexing. Human indexing has had the same problems for over fifty years.
    Source
    Cataloging and classification quarterly. 33(2001) no.1, S.63-75
    Type
    a
  4. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.02 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
    Type
    a
  5. Micco, M.; Popp, R.: Improving library subject access (ILSA) : a theory of clustering based in classification (1994) 0.02 
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    Abstract
    The ILSA prototype was developed using an object-oriented multimedia user interfcae on six NeXT workstations with two databases: the first with 100.000 MARC records and the second with 20.000 additional records enhanced with table of contents data. The items are grouped into subject clusters consisting of the classification number and the first subject heading assigned. Every other distinct keyword in the MARC record is linked to the subject cluster in an automated natural language mapping scheme, which leads the user from the term entered to the controlled vocabulary of the subject clusters in which the term appeared. The use of a hierarchical classification number (Dewey) makes it possible to broaden or narrow a search at will
    Type
    a
  6. Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014) 0.02 
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    Abstract
    Purpose - The purpose of this paper is to explore the potential of applying the Dewey Decimal Classification (DDC) as an established knowledge organization system (KOS) for enhancing social tagging, with the ultimate purpose of improving subject indexing and information retrieval. Design/methodology/approach - Over 11.000 Intute metadata records in politics were used. Totally, 28 politics students were each given four tasks, in which a total of 60 resources were tagged in two different configurations, one with uncontrolled social tags only and another with uncontrolled social tags as well as suggestions from a controlled vocabulary. The controlled vocabulary was DDC comprising also mappings from the Library of Congress Subject Headings. Findings - The results demonstrate the importance of controlled vocabulary suggestions for indexing and retrieval: to help produce ideas of which tags to use, to make it easier to find focus for the tagging, to ensure consistency and to increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both as to conceptual relevance to the user and as to appropriateness of the terminology. Originality/value - No research has investigated the enhancement of social tagging with suggestions from the DDC, an established KOS, in a user trial, comparing social tagging only and social tagging enhanced with the suggestions. This paper is a final reflection on all aspects of the study.
    Type
    a
  7. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.02 
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    Date
    20.10.2000 12:22:23
    Type
    a
  8. Hlava, M.M.K.: Automatic indexing : comparing rule-based and statistics-based indexing systems (2005) 0.02 
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    Source
    Information outlook. 9(2005) no.8, S.22-23
    Type
    a
  9. Shafer, K.: Scorpion Project explores using Dewey to organize the Web (1996) 0.02 
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    a
  10. Kasprzik, A.: Automatisierte und semiautomatisierte Klassifizierung : eine Analyse aktueller Projekte (2014) 0.02 
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    Abstract
    Das sprunghafte Anwachsen der Menge digital verfügbarer Dokumente gepaart mit dem Zeit- und Personalmangel an wissenschaftlichen Bibliotheken legt den Einsatz von halb- oder vollautomatischen Verfahren für die verbale und klassifikatorische Inhaltserschließung nahe. Nach einer kurzen allgemeinen Einführung in die gängige Methodik beleuchtet dieser Artikel eine Reihe von Projekten zur automatisierten Klassifizierung aus dem Zeitraum 2007-2012 und aus dem deutschsprachigen Raum. Ein Großteil der vorgestellten Projekte verwendet Methoden des Maschinellen Lernens aus der Künstlichen Intelligenz, arbeitet meist mit angepassten Versionen einer kommerziellen Software und bezieht sich in der Regel auf die Dewey Decimal Classification (DDC). Als Datengrundlage dienen Metadatensätze, Abstracs, Inhaltsverzeichnisse und Volltexte in diversen Datenformaten. Die abschließende Analyse enthält eine Anordnung der Projekte nach einer Reihe von verschiedenen Kriterien und eine Zusammenfassung der aktuellen Lage und der größten Herausfordungen für automatisierte Klassifizierungsverfahren.
    Type
    a
  11. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.02 
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    Date
    14. 6.2015 22:12:44
    Type
    a
  12. Hauer, M.: Automatische Indexierung (2000) 0.02 
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    Source
    Wissen in Aktion: Wege des Knowledge Managements. 22. Online-Tagung der DGI, Frankfurt am Main, 2.-4.5.2000. Proceedings. Hrsg.: R. Schmidt
    Type
    a
  13. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.02 
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    14. 6.2015 22:12:56
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  14. Hauer, M.: Tiefenindexierung im Bibliothekskatalog : 17 Jahre intelligentCAPTURE (2019) 0.02 
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    B.I.T.online. 22(2019) H.2, S.163-166
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  15. Kuhlen, R.: Experimentelle Morphologie in der Informationswissenschaft (1977) 0.02 
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    63 BGT 1123
  16. Kutschekmanesch, S.; Lutes, B.; Moelle, K.; Thiel, U.; Tzeras, K.: Automated multilingual indexing : a synthesis of rule-based and thesaurus-based methods (1998) 0.01 
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    Information und Märkte: 50. Deutscher Dokumentartag 1998, Kongreß der Deutschen Gesellschaft für Dokumentation e.V. (DGD), Rheinische Friedrich-Wilhelms-Universität Bonn, 22.-24. September 1998. Hrsg. von Marlies Ockenfeld u. Gerhard J. Mantwill
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  17. Stankovic, R. et al.: Indexing of textual databases based on lexical resources : a case study for Serbian (2016) 0.01 
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  18. Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988) 0.01 
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  19. Tsareva, P.V.: Algoritmy dlya raspoznavaniya pozitivnykh i negativnykh vkhozdenii deskriptorov v tekst i protsedura avtomaticheskoi klassifikatsii tekstov (1999) 0.01 
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  20. Tsujii, J.-I.: Automatic acquisition of semantic collocation from corpora (1995) 0.01 
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    Abstract
    Proposes automatic linguistic knowledge acquisition from sublanguage corpora. The system combines existing linguistic knowledge and human intervention with corpus based techniques. The algorithm involves a gradual approximation which works to converge linguistic knowledge gradually towards desirable results. The 1st experiment revealed the characteristic of this algorithm and the others proved the effectiveness of this algorithm for a real corpus
    Date
    31. 7.1996 9:22:19
    Type
    a

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  • a 364
  • el 31
  • m 5
  • x 5
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