Performance measurement and data base design
Alfonso P. Cardenas, Larry F. Bowman, et al.
ACM Annual Conference 1975
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. ©1996 IEEE.
Alfonso P. Cardenas, Larry F. Bowman, et al.
ACM Annual Conference 1975
Yvonne Anne Pignolet, Stefan Schmid, et al.
Discrete Mathematics and Theoretical Computer Science
Fan Zhang, Junwei Cao, et al.
IEEE TETC
B. Wagle
EJOR