Data mining techniques

Research output: Contribution to journalConference articlepeer-review


Data mining, or knowledge discovery in databases, has been popularly recognized as an important research issue with broad applications. We provide a comprehensive survey, in database perspective, on the data mining techniques developed recently. Several major kinds of data mining methods, including generalization, characterization, classification, clustering, association, evolution, pattern matching, data visualization, and meta-rule guided mining, will be reviewed. Techniques for mining knowledge in different kinds of databases, including relational, transaction, object-oriented, spatial, and active databases, as well as global information systems, will be examined. Potential data mining applications and some research issues will also be discussed.

Original languageEnglish (US)
Pages (from-to)545
Number of pages1
JournalSIGMOD Record (ACM Special Interest Group on Management of Data)
Issue number2
StatePublished - 1996
Externally publishedYes
EventProceedings of the 1996 ACM SIGMOD International Conference on Management of Data - Montreal, Can
Duration: Jun 4 1996Jun 6 1996

ASJC Scopus subject areas

  • Software
  • Information Systems


Dive into the research topics of 'Data mining techniques'. Together they form a unique fingerprint.

Cite this