Automatic Document Classification Part II . Additional Experiments

Authors:
Harold Borko;Myrna Bernick
Affiliations:
System Development Corporation, Santa Monica, California;System Development Corporation, Santa Monica, California
Venue:
Journal of the ACM (JACM)
Year:
1964

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Abstract

This study reports the results of a series of experiments in the techniques of automatic document classification. Two different classification schedules are compared along with two methods of automatically classifying documents into categories. It is concluded that, while there is no significant difference in the predictive efficiency between the Bayesian and the Factor Score methods, automatic document classification is enhanced by the use of a factor-analytically-derived classification schedule. Approximately 55 percent of the document were automatically and correctly classified.