Csp-som : a Clustering Method for Web Data
نویسنده
چکیده
Every Organizations need to understand their customer’s behavior, preferences and future needs, which depend on past behavior. Web Usage Mining is an active research topic in which user session clustering is done to understand user’s activities. In this paper, we use Neural based approach Self Organizing Map for clustering of session as a trend analysis with some parameters. It depends on the performance of the clustering of the number of requests. Here we are using SOM algorithm in Closed Frequent Sequential Traversal Pattern Mining called CSP-SOM and generated cluster of web data. In this research we establish good prediction with quantity of data and the quality of the results.
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