Constraint-based, multidimensional data mining

Jiawei Han, Laks V.S. Lakshmanan, Raymond T. Ng

Research output: Contribution to specialist publicationArticle

Abstract

Data mining is most effective when the computer does what it does best, like searching large databases or counting, and users do what they do best, like specifying the current mining session's focus. This division of labor is best achieved through constraint-based mining, in which the user provides restraints that guide a search. Mining can also be improved by employing a multidimensional, hierarchical view of the data. Together, constraint-based and multidimensional techniques can provide more ad hoc, query-driven process that exploits the semantics of data more effectively than stand-alone data mining systems.

Original languageEnglish (US)
Pages46-50
Number of pages5
Volume32
No8
Specialist publicationComputer
DOIs
StatePublished - Aug 1 1999
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)

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    Han, J., Lakshmanan, L. V. S., & Ng, R. T. (1999). Constraint-based, multidimensional data mining. Computer, 32(8), 46-50. https://doi.org/10.1109/2.781634