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Web usage mining using support vector machine.
| Content Provider | CiteSeerX |
|---|---|
| Abstract | Abstract. 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. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Web Page Web Log Record Dynamic Collection Usage Pattern Web Page Access Data Mining Web Usage Mining Process Web Log Data User Access Pattern Web Usage Mining Mine Kdd Cup Recommendation System Large Web Log Data Rich Source Web Usage Mining Uci Machine Support Vector Machine Hyperlink Information User Click Stream Visitor Good Information Usage Information Log Record |
| Content Type | Text |
| Resource Type | Article |
