CLUSTERING OF TEXTUAL DATA BY USING K-MEANS TECHNIQUE

Abstract

Abstract: To store the textual data and various documents, the usage of electronic media is widespread. To retrieve the
important information from the large document collection of unstructured data is a very difficult and time consuming task. It
is easier to find the relevant documents from a huge data collection only when the data collected is in ordered form or the
data is classified by certain group or category. Still the problem persists to find the best grouping technique. This paper
concentrates on the implementation technique of k-means clustering algorithm. K-means technique is used here to cluster the
unlabeled data or the text document collection that is highly unstructured. It begins with the representative model of the
unstructured data and finally generating the set of sorted clusters as a result. Furthermore, the results can be refined by
analyzing the sorted set of clusters.