Thumbnail
Access Restriction
Subscribed

Author Borko, Harold ♦ Bernick, Myrna
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©1964
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
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.
ISSN 00045411
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1964-04-01
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 11
Issue Number 2
Page Count 14
Starting Page 138
Ending Page 151


Open content in new tab

   Open content in new tab
Source: ACM Digital Library