Computer Science – Information Retrieval
Scientific paper
2010-07-25
(IJCSIS) International Journal of Computer Science and Information Security, Vol. 8, No. 2, MAY 2010, pp. 174-180
Computer Science
Information Retrieval
7 pages, 5 figures, 7 tables; Journal Ref: (IJCSIS) ISSN 1947-5500 http://sites.google.com/site/ijcsis/ http://sites.google.
Scientific paper
With the advancement of technology and reduced storage costs, individuals and organizations are tending towards the usage of electronic media for storing textual information and documents. It is time consuming for readers to retrieve relevant information from unstructured document collection. It is easier and less time consuming to find documents from a large collection when the collection is ordered or classified by group or category. The problem of finding best such grouping is still there. This paper discusses the implementation of k-Means clustering algorithm for clustering unstructured text documents that we implemented, beginning with the representation of unstructured text and reaching the resulting set of clusters. Based on the analysis of resulting clusters for a sample set of documents, we have also proposed a technique to represent documents that can further improve the clustering result.
Ali Anis Noor
Mustafa Atika
Safeer Yasir
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