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Please use this identifier to cite or link to this item: https://doi.org/10.1109/5254.889106
DC FieldValue
dc.titleAnalyzing the subjective interestingness of association rules
dc.contributor.authorLiu, B.
dc.contributor.authorHsu, W.
dc.contributor.authorChen, S.
dc.contributor.authorMa, Y.
dc.date.accessioned2013-07-04T07:29:33Z
dc.date.available2013-07-04T07:29:33Z
dc.date.issued2000
dc.identifier.citationLiu, B., Hsu, W., Chen, S., Ma, Y. (2000). Analyzing the subjective interestingness of association rules. IEEE Intelligent Systems and Their Applications 15 (5) : 47-55. ScholarBank@NUS Repository. https://doi.org/10.1109/5254.889106
dc.identifier.issn10947167
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/38905
dc.description.abstractA new approach to help users find interesting rules from a set of discovered association rules is described. This interestingness analysis system (IAS) leverages the user's existing domain knowledge to analyze discovered associations and then rank discovered rules according to various interestingness criteria.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/5254.889106
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/5254.889106
dc.description.sourcetitleIEEE Intelligent Systems and Their Applications
dc.description.volume15
dc.description.issue5
dc.description.page47-55
dc.description.codenIISYF
dc.identifier.isiut000165474500011
Appears in Collections:Staff Publications

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