Title :
Real-time business intelligence system architecture with stream mining
Author :
Hang, Yang ; Fong, Simon
Author_Institution :
Dept. of Comput. & Inf. Sci., Univ. of Macau, Macau, China
Abstract :
Business Intelligence (BI) capitalized on data-mining and analytics techniques for discovering trends and reacting to events with quick decisions. We argued that a new breed of data-mining, namely stream-mining where continuous data streams arrive into the system and get mined very quickly, stimulates the design of a new real-time BI architecture. In the past, stream-mining (especially in algorithmic level) and digital information system architectures have been studied separately. We attempted in this paper to present a unified view on the real-time BI system architecture powered by stream-mining. Some typical applications in which our architecture can support are described.
Keywords :
competitive intelligence; data analysis; data mining; information systems; business intelligence; data analytics; data mining; digital information system architectures; stream mining; Artificial intelligence; Bismuth; Business; Computer architecture; Conferences; Data mining; Real time systems;
Conference_Titel :
Digital Information Management (ICDIM), 2010 Fifth International Conference on
Conference_Location :
Thunder Bay, ON
Print_ISBN :
978-1-4244-7572-8
DOI :
10.1109/ICDIM.2010.5664637