By Topic

Real-time business intelligence system architecture with stream mining

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yang Hang ; Dept. of Comput. & Inf. Sci., Univ. of Macau, Macau, China ; Fong, S.

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.

Published in:

Digital Information Management (ICDIM), 2010 Fifth International Conference on

Date of Conference:

5-8 July 2010