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Jardine, N.; Rijsbergen, C.J. van: ¬The use of hierarchic clustering in information retrieval (1971) 0.01

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Source: Information storage and retrieval. 7(1971), S.217-240

Dattola, R.T.: FIRST: Flexible information retrieval system for text (1979) 0.01

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Source: Journal of the American Society for Information Science. 30(1979), S.9-14

Sparck Jones, K.; Jackson, D.M.: ¬The use of automatically obtained keyword classification for information retrieval (1970) 0.01

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Source: Information storage and retrieval. 5(1970), S.175-201

Sparck Jones, K.: Automatic keyword classification for information retrieval (1971) 0.01

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Gray, W.A.; Harley, A.J.: Computer assisted indexing (1971) 0.01

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Source: Information storage and retrieval. 7(1971), S.167-174

Bookstein, A.; Swanson, D.R.: Probabilistic models for automatic indexing (1974) 0.01

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Source: Journal of the American Society for Information Science. 25(1974), S.312-318

Croft, W.B.: Clustering large files of documents using the single link method (1977) 0.01

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Source: Journal of the American Society for Information Science. 28(1977), S.341-344

Sparck Jones, K.: Index term weighting (1973) 0.01

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Source: Information storage and retrieval. 9(1973), S.619-633

Salton, G.: ¬A new comparison between conventional indexing (MEDLARS) and automatic text processing (SMART) (1972) 0.01

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Source: Journal of the American Society for Information Science. 23(1972), S.75-84

Hafer, M.A.; Weiss, S.F.: Word segmentation by letter successor varieties (1974) 0.01
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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.

Source

Information storage and retrieval. 10(1974) H.11/12, S.371-385

Salton, G.; Wong, A.; Yang, C.S.: ¬A vector space model for automatic indexing (1975) 0.00

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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.

Kuhlen, R.: Experimentelle Morphologie in der Informationswissenschaft (1977) 0.00

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LCSH: Information storage and retrieval systems
Subject: Information storage and retrieval systems

Salton, G.: Fast document classification in automatic information retrieval (1978) 0.00

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