  World Wide Web is a huge repository of information and there is a tremendous
increase in the volume of information daily. The number of users are also
increasing day by day. To reduce users browsing time lot of research is taken
place. Web Usage Mining is a type of web mining in which mining techniques are
applied in log data to extract the behaviour of users. Clustering plays an
important role in a broad range of applications like Web analysis, CRM,
marketing, medical diagnostics, computational biology, and many others.
Clustering is the grouping of similar instances or objects. The key factor for
clustering is some sort of measure that can determine whether two objects are
similar or dissimilar . In this paper a novel clustering method to partition
user sessions into accurate clusters is discussed. The accuracy and various
performance measures of the proposed algorithm shows that the proposed method
is a better method for web log mining.
