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Review of Clustering Techniques for Finding the Similarity in Articles
Author(s) -
Usha Rani,
Shashank Sahu
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016912329
Subject(s) - computer science , similarity (geometry) , cluster analysis , information retrieval , data science , data mining , artificial intelligence , image (mathematics)
Clustering is an important technique in data mining. It is a technique in which grouping of item taken place into the clusters in such a way that items of same cluster have more similarity than the items into another cluster, but is very dissimilar to the item in other clusters. The aim of document clustering is to make a set of clusters of given documents in such a way that document of each cluster have more similarity than the documents of other clusters. This paper reviews various techniques of clustering which can be divided mainly into two groups that are hierarchical and partitional clustering.

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