The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Data Mining for Web-Enabled Electronic Business Applications
|
|
Author(s): Richi Nayak (Queensland University of Technology, Australia)
Copyright: 2003
Pages: 10
Source title:
Architectural Issues of Web-Enabled Electronic Business
Source Author(s)/Editor(s): V.K. Murthy (University of New South Wales at Australian Defence Force Academy, Australia)and Nansi Shi (University of South Australia, Australia)
DOI: 10.4018/978-1-59140-049-3.ch008
Purchase
|
Abstract
Web-enabled electronic business is generating massive amounts of data on customer purchases, browsing patterns, usage times, and preferences at an increasing rate. Data mining techniques can be applied to all the data being collected for obtaining useful information. This chapter attempts to present issues associated with data mining for Web-enabled electronic-business.
Related Content
|
Emrah Arğın.
© 2022.
16 pages.
|
|
Ebru Gülbuğ Erol, Mustafa Gülsün.
© 2022.
17 pages.
|
|
Yeşim Şener.
© 2022.
18 pages.
|
|
Salim Kurnaz, Deimantė Žilinskienė.
© 2022.
20 pages.
|
|
Dorothea Maria Bowyer, Walid El Hamad, Ciorstan Smark, Greg Evan Jones, Claire Beattie, Ying Deng.
© 2022.
29 pages.
|
|
Savas S. Ates, Vildan Durmaz.
© 2022.
24 pages.
|
|
Nusret Erceylan, Gaye Atilla.
© 2022.
20 pages.
|
|
|