Title :
A Framework of Business Intelligence-Driven Data Mining for E-business
Author :
Hang, Yang ; Fong, Simon
Author_Institution :
Dept. of Comput. & Inf. Sci., Univ. of Macau, Macau, China
Abstract :
This paper proposes a data mining methodology called Business Intelligence-driven Data Mining (BIdDM). It combines knowledge-driven data mining and method-driven data mining, and fills the gap between business intelligence knowledge and existent various data mining methods in e-Business. BIdDM contains two processes: a construction process of a four-layer framework and a data mining process. A methodology is established in setting up the four-layer framework, which is an important part in BIdDM. A case study of B2C e-Shop is provided to illustrate the use of BIdDM.
Keywords :
competitive intelligence; data mining; electronic commerce; business intelligence-driven data mining; e-business; knowledge-driven data mining; method-driven data mining; Bismuth; Computer networks; Data mining; Databases; Delta modulation; Information representation; Information retrieval; Information science; Internet; Knowledge representation; BI-driven Data Mining; Business intelligence; Data mining;
Conference_Titel :
INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5209-5
Electronic_ISBN :
978-0-7695-3769-6
DOI :
10.1109/NCM.2009.403