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Information Processing and… | 5 |
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Egghe, L. – Information Processing and Management, 1988
Presents a mathematical theory that can be used to define concentration places of objects within unordered classes. The application to research on the evolution of journals and subject areas is illustrated, and an online method of calculating concentration evolution is described. (1 references) (CLB)
Descriptors: Algorithms, Bibliometrics, Classification, Databases

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

Rada, Roy – Information Processing and Management, 1987
Reviews aspects of the relationship between machine learning and information retrieval. Highlights include learning programs that extend from knowledge-sparse learning to knowledge-rich learning; the role of the thesaurus; knowledge bases; artificial intelligence; weighting documents; work frequency; and merging classification structures. (78…
Descriptors: Algorithms, Artificial Intelligence, Classification, Documentation

Zaki, M.; Elboraey, F. – Information Processing and Management, 1985
Investigates applicability of inverted file processing in magnetic bubble memories by presenting four magnetic bubble memory models as storage mediums: one based on a major-minor loop configuration; one utilizing a decoder design on a magnetic bubble memory chip; and two based on different structural configurations of the first two. (MBR)
Descriptors: Algorithms, Classification, Computer Storage Devices, Data Processing

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