slugDocument Deliver Using Clustering Techniques and Finding Best Cluster

Abstract

Clustering is an important tool in data mining and knowledge discovery. This enables the users to comprehend a large amount of data. We d evelop DSSC (Document Similarity soft clustering), a soft - clustering algorithm based on the similarity function given. DSSC is similar to many other soft clustering algorithms like fuzzy C - means. That is, it starts out with a carefully selected set of init ial clusters, and uses an iterative approach to improve the clusters. At the end, DSSC produces a set of clusters with each document belonging to several potential clusters. This approach only requires a similarity function to be defined properly, and does not rely on any underlying probability assumptions . This allows DSSC to overcome problems of standard soft clustering algorithms mentioned above, without paying any pric e in efficiency (in fact, we perform K - means based algorithm in many case.

Authors and Affiliations

Jyoti, Neha kaushik, Rekha

Keywords

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  • EP ID EP18075
  • DOI -
  • Views 330
  • Downloads 9

How To Cite

Jyoti, Neha kaushik, Rekha (2014). slugDocument Deliver Using Clustering Techniques and Finding Best Cluster. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(5), -. https://europub.co.uk/articles/-A-18075