An Efficient Algorithm for Document Clustering in Information Retrieval
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 12
Abstract
Document clustering is a set of documents can be divided into similar groups called clusters, so that documents within a cluster have high similarity in comparison to other documents in different clusters. It has been considered intensively due to the fact of its extensive applicability in various areas like information retrieval, web mining and search engines like Google. It is determining the similarity between documents and based on the similarity it will group the documents together. It offers efficient representation and visualization of the documents; thus helps in convenient navigation also. The main objective of this research work is to cluster the documents into similar groups based on the content of the documents. In order to perform this task this research work uses two existing documents clustering algorithms, namely K-means and DBSCAN and also this work proposes a new clustering algorithm, E-DBSCAN. From the experimental results it is observed that the E-DBSCAN gives the better clustering accuracy than other algorithms.
Authors and Affiliations
Ms. R. Janani, Dr. S. Vijayarani
Keywords
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- EP ID EP22903
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