A Review: Techniques for Clustering of Web Usage Mining
Rupinder Kaur, Simarjeet Kaur
In the area of software; data mining technology has been considered as important mean for discovering patterns and trends of large amount of data. So; this approach is basically used to extract the unknown pattern from the large set of data for business as well as real time applications. Data mining is a computational intelligence discipline which has emerged as a effective tool for data analysis; new KDD and good decision making. The raw and unlabeled data from the large volume of dataset can be classified initially in an unsupervised fashion by using cluster analysis i.e. clustering the work of a set of observations into clusters so that observations in the same cluster may be in some sense be treated as similar. The result of the clustering method and efficiency of its domain application are generally determined through various algorithms. This paper includes various clustering algorithms which can use efficiently according to the particular application; available software hardware facilities and size of dataset.
Keywords: Web usage mining, clustering requirements, clustering techniques and algorithms
Edition: Volume 3 Issue 5, May 2014
Pages: 1541 - 1545