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Hoyle, W. G. – Information Storage and Retrieval, 1973
A system of automatic indexing based on Baye's theorem is described briefly. (18 references) (Author)
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
Yu, Clement T. – Information Storage and Retrieval, 1974
Heuristic methods for the construction of term classes are presented and experimental results are obtained to illustrate the usefulness of the method. (Author/PF)
Descriptors: Algorithms, Automatic Indexing, Classification, Cluster Grouping
Bichteler, Julie; Parsons, Ronald G. – Information Storage and Retrieval, 1974
An automatic classification technique using patterns formed by citations in document bibliographies was found to give 62 percent precision and 45 percent recall in a sample file of physics documents. (PF)
Descriptors: Algorithms, Automatic Indexing, Bibliographies, Citations (References)
Peer reviewed Peer reviewed
Craven, Timothy C. – Journal of Documentation, 1987
Describes a microcomputer-based string index format generated from concept networks using multiple search terms. Link weighting is highlighted as a method to decide which term appears first so the entry reflects the classification implied by the search specification. The computer software used for this system is briefly described. (Author/LRW)
Descriptors: Algorithms, Automatic Indexing, Classification, Computer Software
Peer reviewed Peer reviewed
Kar, Gautam; White, Lee J. – Information Processing and Management, 1978
Investigates the feasibility of using a distance measure for automatic sequential document classification. This property of the distance measure is used to design a sequential classification algorithm which classifies key words and analyzes them separately in order to assign primary and secondary classes to a document. (VT)
Descriptors: Algorithms, Automatic Indexing, Classification, Information Processing
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White, Lee J.; And Others – 1975
The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
Peer reviewed Peer reviewed
Willett, Peter – Information Processing and Management, 1981
Describes a fast algorithm for comparing the lists of terms representing documents in automatic classification experiments. Complexity and running time for the algorithm are compared to other procedures, and a short algol-like routine is presented in the appendix. Eight references are included. (Author/BK)
Descriptors: Algorithms, Automatic Indexing, Classification, Documentation
Kar, B. Gautam; White, Lee J. – 1975
The feasibility of using a distance measure, called the Bayesian distance, for automatic sequential document classification was studied. Results indicate that, by observing the variation of this distance measure as keywords are extracted sequentially from a document, the occurrence of noisy keywords may be detected. This property of the distance…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
Peer reviewed Peer reviewed
Enser, P. G. B. – Journal of Documentation, 1985
Investigates techniques for automatic classification of book material focusing on: computer-based surrogation of monographic material, book surrogate clustering on basis of content association, evaluation of resultant classifications. Test collection (250 books) is described with surrogation by means of back-of-the-book index, table of contents,…
Descriptors: Algorithms, Automatic Indexing, Books, Classification