Online and Incremental Mining of Separately-Grouped Web Access Logs
Conference Proceeding Article
The rising popularity of electronic commerce makes data mining an indispensable technology for business competitiveness. The World Wide Web provides abundant raw data in the form of web access logs, web transaction logs and web user profiles. Without data mining tools, it is impossible to make any sense of such massive data. In this paper, we focus on web usage mining because it deals most appropriately with understanding user behavioral patterns which is the key to successful customer relationship management. Previous work deals separately on specific issues of web usage mining and make assumptions without taking a holistic view and thus, have limited practical applicability. We formulate a novel and more holistic version of web usage min-ing termed TRAnsactionized LOgfile Mining (TRALOM) to effectively and correctly identify transactions as well as to mine useful knowledge from web access logs. We also introduce a new data structure, called the Webrie, to efficiently hold useful preprocessed data so that TRALOM can be done in an online and incremental fashion. Experiments conducted on real web server logs verify the usefulness and practicality of our proposed techniques.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Proceedings of the third International Conference on Web Information Systems Engineering: WISE 2002: 12-14 December 2002, Singapore
City or Country
WOON, Yew-Kwong; NG, Wee-Keong; and LIM, Ee Peng.
Online and Incremental Mining of Separately-Grouped Web Access Logs. (2002). Proceedings of the third International Conference on Web Information Systems Engineering: WISE 2002: 12-14 December 2002, Singapore. 53-62. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1016