Title :
Granular fuzzy Web intelligence techniques for profitable data mining
Author :
Zhang, Yan-Qing ; Shteynberg, M. ; Prasad, S.K. ; Sunderraman, R.
Author_Institution :
Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA
Abstract :
Data mining has a lot of e-commerce applications. The key problem is how to find useful hidden patterns for better business applications. For these problems, granular fuzzy Web intelligence techniques are used to implement the granular fuzzy Web data mining system for available historical data of the credit company customers. Fuzzy computing and granular computing are used to design the Web fuzzy-interval data mining system that can do fuzzy-interval data clustering under uncertainty.
Keywords :
Internet; customer profiles; data mining; electronic commerce; fuzzy logic; Web intelligence techniques; business application; credit company customers; e-commerce applications; fuzzy computing; fuzzy interval data clustering; granular computing; granular fuzzy techniques; hidden patterns; profitable data mining; uncertain systems; Competitive intelligence; Computational intelligence; Computer networks; Credit cards; Data mining; Fuzzy logic; Fuzzy systems; Intelligent networks; Loans and mortgages; Wireless networks;
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
DOI :
10.1109/FUZZ.2003.1206648
