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A Life Cycle on Processing Large Dataset - LCPL

by Rajit Nair, Amit Bhagat
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 53
Year of Publication: 2018
Authors: Rajit Nair, Amit Bhagat
10.5120/ijca2018917382

Rajit Nair, Amit Bhagat . A Life Cycle on Processing Large Dataset - LCPL. International Journal of Computer Applications. 179, 53 ( Jun 2018), 27-34. DOI=10.5120/ijca2018917382

@article{ 10.5120/ijca2018917382,
author = { Rajit Nair, Amit Bhagat },
title = { A Life Cycle on Processing Large Dataset - LCPL },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2018 },
volume = { 179 },
number = { 53 },
month = { Jun },
year = { 2018 },
issn = { 0975-8887 },
pages = { 27-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number53/29541-2018917382/ },
doi = { 10.5120/ijca2018917382 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:59:08.182845+05:30
%A Rajit Nair
%A Amit Bhagat
%T A Life Cycle on Processing Large Dataset - LCPL
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 53
%P 27-34
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

We all know that today’s era is of big data, we can also call it as large data set where data from different sources are collected at one place and it is very difficult to process these type of data. Mainly these types of data are collected where there is huge volume, high velocity and different varieties of data. These types of data are processed for analytical purpose because if we did not analyze it then there is no sense of collecting these type of data. So in this paper we are explaining about the life cycle of processing large data set and propose a new term for it i.e. LCPLD(Life Cycle on Processing Large Data set. Here the discussion will mainly focus on the steps which are involved during the life cycle of processing that are pre-processing, feature selection, feature extraction, classification, clustering and many more.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Preprocessing Features Classification Clustering Dimensions Features.

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