• DocumentCode
    1279135
  • Title

    Data mining: an overview from a database perspective

  • Author

    Chen, Ming-Syan ; Han, Jiawei ; Yu, Philip S.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • Volume
    8
  • Issue
    6
  • fYear
    1996
  • fDate
    12/1/1996 12:00:00 AM
  • Firstpage
    866
  • Lastpage
    883
  • 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
  • Keywords
    Internet; deductive databases; generalisation (artificial intelligence); information services; knowledge acquisition; learning (artificial intelligence); pattern matching; reviews; very large databases; Internet; association rules; business opportunities; classification; comparative study; data characterization; data clustering; data cubes; data generalization; data mining; data warehousing; information-providing services; knowledge discovery; large databases; machine learning; multiple-dimensional databases; online services; overview; pattern matching algorithms; user behavior; Business; Data engineering; Data mining; Engineering management; Learning; Power engineering and energy; Power system management; Relational databases; Spatial databases; US Government;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.553155
  • Filename
    553155