Efficient Clustering Algorithm to Discover User Pattern Applying on Weblog Data

WWW has becomes today not only an accessible and searchable information source but also one of the most important communication channels. One of the key steps in Knowledge Discovery in Databases is to create a suitable target data set for the data mining. Clustering of data is a method by which large sets of data is grouped into clusters of smaller sets of similar data.K-means clustering algorithm suffers from two major shortcomings, right value of clusters (k) are initially unknown and effective selections of initial seed are also difficult. In this dissertation, the efficient algorithm is proposed which overcomes initial seed problem and also the validation of cluster problem. The comparison is performed between proposed fuzzy clustering algorithm, fuzzy C-means and K-mean clustering algorithm on web log dataset to test its accuracy and efficiency.