Hierarchical Document Clustering Using Closed Itemsets with Comparision Using Weka Tools

In Today's world huge amount of knowledge is propagated and stored in text databases over the large networks. This leads to increment in the numbers of document files. So we need a vigorous and skillful way to group this large amount of data. Clustering is the finest tool of data mining for regulating and harmonizing information. Clustering outline the similar objects or data into one cluster and different objects into another one based on their measurement of diminishing inter similarity and overestimating intra dissimilarity. However most of the clustering techniques face many issues like high dimensionality, scalability, accuracy, etc. Document clustering is an unsupervised clustering method for organizing documents, and providing fast information retrieval or filtering. This paper will present a review on some document clustering methods and proposal of a new one approach for hierarchical document clustering using closed item-sets.