Title of program: JETSET 6.3 Catalogue number: AATJ Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland (see application form in this issue) Computer for which the program is de...
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Title of program: JETSET 6.3 Catalogue number: AATJ Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland (see application form in this issue) Computer for which the program is designed and others on which it is operable: ND, VAX, IBM, CDC and others with a FORTRAN 77 compiler Computer: ND-570; Installation: University of Lund, Lund, Sweden Operating system: SINTRAN III - VSX/500 Programming language used: FORTRAN 77 High speed storage required: 50 Kwords No. of bits in word: 32 Peripherals used: terminal for input, terminal or line printer for output No. of lines in combined program and test deck: 6173
A strategy is given for selecting the dimensionr of the linear variety which is used to define the criterion functionalJ vrm and which determines the shape of the data clusters detected by the correspondingc-Varieties...
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A strategy is given for selecting the dimensionr of the linear variety which is used to define the criterion functionalJ vrm and which determines the shape of the data clusters detected by the correspondingc-Varieties (FCV) clustering algorithms.
An automatic document clustering procedure is described which does not require the use of an inter-document similar ity matrix and which is independent of the order in which the documents are processed. The procedure ...
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An automatic document clustering procedure is described which does not require the use of an inter-document similar ity matrix and which is independent of the order in which the documents are processed. The procedure makes use of an initial set of clusters which is derived from certain of the terms in the indexing vocabulary used to characterise the documents in the file. The retrieval effectiveness obtained using the clustered file is compared with that obtained from serial searching and from use of the single-linkage clustering method.
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