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Market Analysis and Review Synthesis

S. R. Gosavi1 , P.R. Gohad2 , P.P. Sandanshi3 , S.T. Mahajan4 , N.R. Wankhade5

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-3 , Page no. 64-66, Mar-2014

Online published on Mar 30, 2014

Copyright © S. R. Gosavi, P.R. Gohad, P.P. Sandanshi, S.T. Mahajan, N.R. Wankhade . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. R. Gosavi, P.R. Gohad, P.P. Sandanshi, S.T. Mahajan, N.R. Wankhade, “Market Analysis and Review Synthesis,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.3, pp.64-66, 2014.

MLA Style Citation: S. R. Gosavi, P.R. Gohad, P.P. Sandanshi, S.T. Mahajan, N.R. Wankhade "Market Analysis and Review Synthesis." International Journal of Computer Sciences and Engineering 2.3 (2014): 64-66.

APA Style Citation: S. R. Gosavi, P.R. Gohad, P.P. Sandanshi, S.T. Mahajan, N.R. Wankhade, (2014). Market Analysis and Review Synthesis. International Journal of Computer Sciences and Engineering, 2(3), 64-66.

BibTex Style Citation:
@article{Gosavi_2014,
author = {S. R. Gosavi, P.R. Gohad, P.P. Sandanshi, S.T. Mahajan, N.R. Wankhade},
title = {Market Analysis and Review Synthesis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2014},
volume = {2},
Issue = {3},
month = {3},
year = {2014},
issn = {2347-2693},
pages = {64-66},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=70},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=70
TI - Market Analysis and Review Synthesis
T2 - International Journal of Computer Sciences and Engineering
AU - S. R. Gosavi, P.R. Gohad, P.P. Sandanshi, S.T. Mahajan, N.R. Wankhade
PY - 2014
DA - 2014/03/30
PB - IJCSE, Indore, INDIA
SP - 64-66
IS - 3
VL - 2
SN - 2347-2693
ER -

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Abstract

For the analysis of business, a lot of research attention in the field of computational statistics and data mining has been made. Due to recent technological advances in the field of data clustering, the researchers face ever-increasing challenges in extracting relevant information from enormous volumes of available data. The paper focus on large data sets obtained from online web visiting and categorizing this into clusters according some similarity it helpful tool for the top level management to take optimized and beneficial decisions of business expansion. Clustering is the assignment of a set of observations into subsets. Cluster analysis is widely used in market research when working with multivariate data from surveys. Market researcher partition the general population of consumers into market segments and understand the relationships between customers.

Key-Words / Index Term

System Architecture, Cluster, Porter Stemmer Algorithm

References

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