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Data mining: an overview from a database perspective
- Source :
- IEEE Transactions on Knowledge and Data Engineering. 8:866-883
- Publication Year :
- 1996
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 1996.
-
Abstract
- 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 online services over the Internet, also call for various data mining techniques to better understand user behavior, to improve the service provided and to increase business opportunities. In response to such a demand, this article provides 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.
- Subjects :
- Association rule learning
Knowledge representation and reasoning
Relational database
Computer science
computer.software_genre
World Wide Web
Data cube
Text mining
Knowledge extraction
Information system
Cluster analysis
Database
business.industry
Data manipulation language
InformationSystems_DATABASEMANAGEMENT
Data science
Knowledge acquisition
Data warehouse
Computer Science Applications
Computational Theory and Mathematics
Web mining
The Internet
Data mining
business
computer
Information Systems
Subjects
Details
- ISSN :
- 10414347
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Knowledge and Data Engineering
- Accession number :
- edsair.doi...........51dc2742ab9060496e4a54e6a38d5831