An Improved Approach for Web Document Clustering

With an ever increasing volume of data, terabytes of text data is being generated everyday in the form of semi structured, unstructured and structured data via various sources. Efficiency of clusters is the major concern when dealing with application areas of clustering like information retrieval. In this paper K-means clustering approach is applied based on similarity measure among the documents. Further optimization technique specifically bio- inspired is used to intelligently explore and re-adjust the documents from the pre-organized clusters followed by a classification approach for the evaluation and validation of the clusters.