Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Data mining: concepts and techniques
Data mining: concepts and techniques
Machine Learning
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Web usage mining using evolutionary support vector machine
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
A competitive co-evolving support vector clustering
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
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The web contains rich and dynamic collections of hyperlink information, web page access, and usage information providing rich sources for data mining. From this, we need a system to recommend a visitor good information. This recommendation system can be constructed by web usage mining process. The web usage mining mines web log records to discover user access patterns of web pages. Also it is the application of data mining techniques to large web log data in order to extract usage patterns from user's click streams. In general, the size of web log records is so large that we have difficulty to analyze web log data. To make matter worse, the web log records are very sparse. So it is very hard to estimate the dependency between the web pages. In this paper, we solved this difficulty of web usage mining using support vector machine. In the experiments, we verified our proposed method by given data from UCI machine learning repository and KDD cup 2000.