.png){kind=icon}
Return
Data mining: An overview from a database perspective
.png){kind=icon}
PRE
AI
DOI：10.1109/69.553155.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
data mining
knowledge discovery
association rules
classification
data clustering
pattern matching algorithms
data generalization and characterization
data cubes
multiple-dimensional databases
Journal
IF:
10.4
Papers:
6.8K
Citations:
3.2W
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSaveShareSave
ShareSaveShareSave
View more