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Feinman, R. D.; Kwok, K. L. – Journal of the American Society for Information Science, 1973
A study was undertaken to classify mechanically a document collection using the free-language words in titles and abstracts of physics research papers. Using a clustering algorithm, results were obtained which closely duplicated clusters obtained by previous experiments with citations. A brief comparison is made with a traditional manual…
Descriptors: Algorithms, Classification, Cluster Analysis, Databases

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

Ribeiro-Neto, Berthier; Laender, Alberto H. F.; de Lima, Luciano R. S. – Journal of the American Society for Information Science and Technology, 2001
Evaluates the retrieval performance of an algorithm that automatically categorizes medical documents, which consists in assigning an International Code of Disease (ICD) based on well-known information retrieval techniques. Reports on experimental results that tested precision using a database of over 20,000 medical documents. (Author/LRW)
Descriptors: Algorithms, Automation, Classification, Databases

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
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