Authors:
Pradeep kumar
1
;
P. Radha Krishna
1
;
Supriya kumar De
2
and
S Bapi Raju
3
Affiliations:
1
Institute for Development and Research in Banking Technology, (IDRBT), India
;
2
XLRI Jamshedpur, C.H.Area(E ), India
;
3
University ofHyderabad, India
Keyword(s):
Data mining, rough sets, clickstream, web usage mining , similarity upper approximation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Tremendous growth of the web world incorporates application of data mining techniques to the web logs. Data Mining and World Wide Web encompasses an important and active area of research. Web log mining is analysis of web log files with web pages sequences. Web mining is broadly classified as web content mining, web usage mining and web structure mining. Web usage mining is a techniques to discover usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. This paper demonstrates a rough set based upper similarity approximation method to cluster the web usage pattern. Results were presented using clickstream data to illustrate our technique.