Web Usage Mining to Discover Visitor Group with Common Behavior Using DBSCAN Clustering Algorithm

Web Usage Mining is application of data mining techniques to discover interesting usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Analyzing data through web usage mining can help effective Web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis and so on. The aim of this paper is to emphasize on finding visitor group with common behavior from web log file of website. Web usage mining includes three phases namely preprocessing, pattern discovery and pattern analysis. Web Log file is considered as input here. This paper gives detailed description of how data from Web Log file are used for finding visitor's having common behavior using DBSCAN clustering algorithm.

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