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A Review of Clustering Methods and its Challenges in Document Clustering

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The explosive growth of the Internet and its services with massive amounts of text documents demands for collecting most similar documents together for diverse applications drawing the attention of researchers in this area. Document clustering can simplify the works of document organization needed for various data mining activities for the search engines, data filtering, information classification etc. However, there have been some attempts to build up well-organized document clustering algorithms, but most clustering methods have had difficulty dealing with high dimensional, scalability, accuracy, and important cluster label problems. It contributes a significant function in "machine learning, data mining, information retrieval and pattern recognition". This paper presents a reconsider on different clustering methods in data mining initially. It will focus on the documents clustering mechanism, its applicability, and limitations in documents clustering. Finally, we consider the related works proposed on document clustering and its outcomes.

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Clustering methods, Document Clustering, Data Mining

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"A Review of Clustering Methods and its Challenges in Document Clustering", International Journal of Emerging Technologies and Innovative Research ( | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 11, page no. pp54-60, November-2017, Available at : &

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Published Paper ID: JETIR1711012
Registration ID: 170845
Published In: Volume 4 | Issue 11 | Year November-2017
DOI (Digital Object Identifier):
Page No: 54-60
ISSN Number: 2349-5162

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