A methodology for integrating and exploiting data mining techniques in the design of data warehouses

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aut.conference.typePaper Published in Proceedings
aut.relation.endpage367
aut.relation.pages7
aut.relation.startpage361
aut.researcherPears, Russel Lawrence
dc.contributor.authorUsman, M
dc.contributor.authorPears, R
dc.date.accessioned2013-02-26T04:43:13Z
dc.date.available2013-02-26T04:43:13Z
dc.date.copyright2010
dc.date.issued2010
dc.description.abstractData Warehousing and Data Mining are two mature disciplines in their own right. Yet, they have developed largely separate from each other, despite the fact that techniques developed for pattern recognition such as Clustering and Visualization in the Data Mining discipline have much to offer in the design of Data Warehouses. This is somewhat surprising, given that the two disciplines have broadly the same set of objectives, although the techniques that they employ are admittedly quite different from each other. This may be due to the lack of a suitable methodology for integrating methods such as clustering and pattern visualization into data warehousing design. In this research, we propose such a methodology and report on its application to two case studies involving real world data taken from the UCI Machine Learning repository. We demonstrate how data clustering and visualization methods, working in conjunction with each other can be used to gain new insights and build more meaningful dimensions which may not be obvious to human data warehouse designers.
dc.identifier.citation2nd International Conference on Data Mining and Intelligent Information Technology Applications, Seoul, South Korea, pp.361 - 367 (7)
dc.identifier.urihttps://hdl.handle.net/10292/5195
dc.publisherIEEE
dc.relation.urihttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5713475&tag=1
dc.rightsCopyright © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.accessrightsOpenAccess
dc.subjectAutomatic schema
dc.subjectClustering
dc.subjectData mining
dc.subjectMultidimensional analyis
dc.subjectWarehouseing
dc.titleA methodology for integrating and exploiting data mining techniques in the design of data warehouses
dc.typeConference Contribution
pubs.elements-id7205
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/School of Computing & Mathematical Science
pubs.organisational-data/AUT/PBRF Researchers
pubs.organisational-data/AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers
pubs.organisational-data/AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers/DCT C & M Computing
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