Clustering Technique on Search Engine Dataset Using Data Mining Tool

Unlabeled document collections are becoming increasingly common and mining such databases becomes a major challenge. It is a major issue to retrieve good websites from the larger collections of websites. As the number of available Web pages grows, it is become more difficult for users finding documents relevant to their interests. Clustering is the classification of a data set into subsets (clusters), so that the data in each subset share some common trait - often proximity according to some defined distance measure. By clustering we improve the quality of websites by grouping similar websites in groups. This paper addresses the applications of data mining tool Weka by applying k means clustering to find clusters from huge data sets and find the attributes that govern optimization of search engines.