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dc.contributor.authorCunningham, Sally Jo
dc.contributor.authorSummers, Brent
dc.date.accessioned2008-10-21T00:25:19Z
dc.date.available2008-10-21T00:25:19Z
dc.date.issued1995-06
dc.identifier.citationCunningham, S. J. & Summers, B.(1995). Applying machine learning to subject classification and subject description for information retrieval. (Working paper 95/20). Hamilton, New Zealand: University of Waikato, Department of Computer Science.en_US
dc.identifier.issn1170-487X
dc.identifier.urihttps://hdl.handle.net/10289/1097
dc.description.abstractThis paper describes an experiment in applying standard supervised machine learning algorithms (C4.5 and Induct) to the problem of developing subject classification rules for documents. These algorithms are found to produce surprisingly concise models of document classifications. While the models are highly accurate on the training sets, evaluation over test sets or through cross-validation shows a significant decrease in classification accuracy. Given the difficult nature of the experimental task, however, the results of this investigation are promising and merit further study. An additional algorithm, 1R, is shown to be highly effective in generating lists of candidate terms for subject descriptions.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Waikato, Department of Computer Scienceen_US
dc.relation.ispartofseriesComputer Science Working Papers
dc.subjectcomputer scienceen_US
dc.titleApplying machine learning to subject classification and subject description for information retrievalen_US
dc.typeWorking Paperen_US
uow.relation.series95/20


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