Abstract
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 language | English (US) |
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Pages (from-to) | 545 |
Number of pages | 1 |
Journal | SIGMOD Record (ACM Special Interest Group on Management of Data) |
Volume | 25 |
Issue number | 2 |
DOIs | |
State | Published - 1996 |
Externally published | Yes |
Event | Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data - Montreal, Can Duration: Jun 4 1996 → Jun 6 1996 |
ASJC Scopus subject areas
- Software
- Information Systems