Customer/User segmentation has been a critical element of the marketing and is one of the most important strategic concepts contributed by the marketing discipline to business firms. User Segmentation is the process of developing effective schemes for categorizing and organizing meaningful groups of customers. A user segment is a group of prospects or customers who are selected from a database based on characteristics they possess or exhibit. It also allows company to differentially treat consumers in different segments. User Profiling is the process of analyzing the customers of each segment in order to generalize, describe or name this set of customers based on common characteristics. It is the process of understanding and labeling a
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Traditional clustering  is used to segment the web users or web pages in to groups based on the existing similarities. When a clustering method is used for grouping users, it typically partitions users according to their similarity of browsing behavior under all pages. However, it is often the case that some users behave similarly only on a subset of pages and their behavior is not similar over the rest of the pages. Therefore, traditional clustering methods fail to identify such user groups.
To overcome this problem, concept of Biclustering was introduced. Biclustering[3,4,11] was first introduced by Hartigan . Biclustering is the simultaneous clustering technique. In literature, biclustering algorithms are widely applied to the gene expression data. In this paper, it is used to mine clickstream data in order to extract target usage groups. These groups are analyzed to determine user’s behavior which is an important element in the E-Commerce applications.
The rest of the paper is organized as follows. In Section 2, some of the existing work related to the biclustering approaches and user segmentations are discussed. Methods and materials required for biclustering approach are described in the section 3. Section 3 focuses on the proposed Biclustering approach using Genetic Algorithm. Analysis of experimental results is discussed in the Section 4. Section