  Web Usage mining is a very important tool to extract the hidden business
intelligence data from large databases. The extracted information provides the
organizations with the ability to produce results more effectively to improve
their businesses and increasing of sales. Co-clustering is a powerful
bipartition technique which identifies group of users associated to group of
web pages. These associations are quantified to reveal the users' interest in
the different web pages' clusters. In this paper, Fuzzy Co-Clustering algorithm
is proposed for clickstream data to identify the subset of users of similar
navigational behavior /interest over a subset of web pages of a website.
Targeting the users group for various promotional activities is an important
aspect of marketing practices. Experiments are conducted on real dataset to
prove the efficiency of proposed algorithm. The results and findings of this
algorithm could be used to enhance the marketing strategy for directing
marketing, advertisements for web based businesses and so on.
