An Efficient Approach for Extracting Usage Pattern from Web Log Using Web Usage Mining
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
In today’s world most of the tasks are done by Internet. User spends number of hours over the Internet. So by knowing the behaviour of user to access the Internet we can get lots of information about interest of user. Web usage mining is the process to identify the user’s behaviour in terms of access the Internet. It is the sub part of web mining. It focuses on the techniques that discover the usage pattern from web log. It uses the data mining techniques like association rule analysis, clustering, classification and machine learning. Before applying these techniques to web log some data preprocessing steps are needed for prepare the data. After that pattern discovery techniques are applied to find some interesting pattern. Clustering is one of the data mining techniques to make a group of user or user session having similar characteristics. Data pre-processing are perform using java and sql. After that proposed a new approach for web usage mining is hybridize a Black-Hole with K-means algorithm for clustering of web log data. Black-Hole approach is inspired by nature and relay on concept of black-hole phenomena. From analysis it is proved that Black-hole with KMeans algorithm is an efficient approach for clustering.
Authors and Affiliations
Nirali H. Panchal, Ms. Ompriya Kale
Keywords
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