Data mining: An overview from a database perspective

被引:1166
作者
Chen, MS
Han, JW
Yu, PS
机构
[1] SIMON FRASER UNIV, SCH COMP SCI, BURNABY, BC V5A 1S6, CANADA
[2] IBM CORP, THOMAS J WATSON RES CTR, YORKTOWN HTS, NY 10598 USA
基金
加拿大自然科学与工程研究理事会;
关键词
data mining; knowledge discovery; association rules; classification; data clustering; pattern matching algorithms; data generalization and characterization; data cubes; multiple-dimensional databases;
D O I
10.1109/69.553155
中图分类号
TP18 [人工智能理论];
学科分类号
081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];
摘要
Mining information and knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an important area with an opportunity of major revenues. Researchers in many different fields have shown great interest in data mining. Several emerging applications in information providing services, such as data warehousing and on-line services over the Internet, also call for various data mining techniques to better understand user behavior, to improve the service provided, and to increase the business opportunities. In response to such a demand, this article is to provide a survey, from a database researcher's point of view, on the data mining techniques developed recently. A classification of the available data mining techniques is provided, and a comparative study of such techniques is presented.
引用
收藏
页码:866 / 883
页数:18
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