Data Mining of Web Access Logs Using Classification Techniques
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2014, Vol 2, Issue 8
Abstract
This paper focus on classification, technological advancement, business have gone online. Because of the growing popularity of the World Wide Web. Many website typically experience Lac of visitors every day. Data mining techniques such as association rules, classification, and clustering and attribute selection are considered very useful in web usage mining. Data Mining is gaining more popularity because of its power to extract knowledge from voluminous data where it is beyond the reach of traditional techniques of knowledge discovery and human comprehension. A data mining tool, WEKA is used. The WEKA is a collection of machine learning algorithms for solving real-world data mining problems.
Authors and Affiliations
Md. Azam, Asst. Prof. Md. Tabrez Nafis
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