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Lustig, G.: Methoden der automatischen Indexierung (1970)
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- Source
- Sprachliche Ansätze im Informations- und Dokumentationsbereich. Referate der Arbeitstagung des Komitees Automation der Dokumentation des DGD am 24.-25.2.1970 in Frankfurt
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Kuhlen, R.: Experimentelle Morphologie in der Informationswissenschaft (1977)
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- Content
- Zugl.: Regensburg, Univ., Diss. u.d.T.: Kuhlen, Rainer: Flexine und Derivative in der maschinellen Verarbeitung englischer Texte
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Panyr, J.: STEINADLER: ein Verfahren zur automatischen Deskribierung und zur automatischen thematischen Klassifikation (1978)
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¬The smart retrieval system : experiments in automatic document processing (1971)
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Jardine, N.; Rijsbergen, C.J. van: ¬The use of hierarchic clustering in information retrieval (1971)
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Salton, G.; Yang, C.S.: On the specification of term values in automatic indexing (1973)
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Salton, G.; Wong, A.; Yang, C.S.: ¬A vector space model for automatic indexing (1975)
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- Footnote
- Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.273-280.
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Salton, G.: Fast document classification in automatic information retrieval (1978)
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- Abstract
- A classified or clustered file is one where related or similar records are grouped into classes or clusters of items in such a way that all itmes within a cluster are jointly retrievable. Clustered files are easily adapted to to broad and narrow search strategies, and simple file updating methods are available. An inexpensive file clustering method applicable to large files is given together with appropriate file search methods
- Source
- Kooperation in der Klassifikation I. Proc. der Sekt.1-3 der 2. Fachtagung der Gesellschaft für Klassifikation, Frankfurt-Hoechst, 6.-7.4.1978. Bearb.: W. Dahlberg
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Hafer, M.A.; Weiss, S.F.: Word segmentation by letter successor varieties (1974)
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- Abstract
- This paper describes a method for automatically segmenting words into their stems and affixes. The process uses certain statistical properties of corpus (successor and predecessor letter variety counts) to indicate where words should be divided. Consequently, this process is less reliant on human intervention than are other methods for automated stemming. The segmentation system is used to construct stem dictionariesfor documnet classification. Information retrieval experiments are then performed using documents and queries so classified. Results show not only that this method is capable of high quality word segmentation, but also that its use in information retrieval produce results that are at least as good as thosse obtained using the more traditional stemming process.
