The partitional clustering concept started with K-means algorithm which was published in
1957. Since then many classical partitional clustering algorithms have been reported based …

Optimization based pattern discovery has emerged as an important field in knowledge
discovery and data mining (KDD), and has been used to enhance the efficiency and …

With advancement of the technology, data size is increasing rapidly. For making intelligent
decisions based on data, efficacious analytic methods are required. Data clustering, a …

The bee colony optimization (BCO) algorithm is proved to be one of the fast, robust and
efficient global search heuristics in tackling different practical problems. Considering BCO …

Web applications are increasing at an enormous speed and its users are increasing at
exponential speed. The evolutionary changes in technology have made it possible to …

Data clustering is one of the most widely used data mining techniques, classifying similar
data items into groups on the basis of similarity among the data items. Different issues have …

In Current era, internet is playing such a vital role in our everyday life that it is very difficult to
survive without it. The World Wide Web (WWW) has influenced a lot to both users (visitors) …

Clustering-an important data mining task, which groups the data on the basis of similarities
among the data, can be divided into two broad categories, partitional clustering and …

Due to a marked increase in the number of web users and their activities, many application
areas that use patterns generated from their activities has been proposed. Web-based …

Websites on the internet are useful source of information in our day-to-day activity. Web
Usage Mining (WUM) is one of the major applications of data mining, artificial intelligence …