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An Efficient Record Linkage Technique for Handling BIG DATA

by Sneha Ambhore, Shailvi Maurya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 1
Year of Publication: 2018
Authors: Sneha Ambhore, Shailvi Maurya
10.5120/ijca2018917442

Sneha Ambhore, Shailvi Maurya . An Efficient Record Linkage Technique for Handling BIG DATA. International Journal of Computer Applications. 182, 1 ( Jul 2018), 56-58. DOI=10.5120/ijca2018917442

@article{ 10.5120/ijca2018917442,
author = { Sneha Ambhore, Shailvi Maurya },
title = { An Efficient Record Linkage Technique for Handling BIG DATA },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 182 },
number = { 1 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 56-58 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number1/29729-2018917442/ },
doi = { 10.5120/ijca2018917442 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:10:08.007974+05:30
%A Sneha Ambhore
%A Shailvi Maurya
%T An Efficient Record Linkage Technique for Handling BIG DATA
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 1
%P 56-58
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The word BIG DATA is nothing but huge amount of data generated through all the sources including social networking sites like facebook, twitter, Intstagram etc. this data sometimes may be repetitive that is same person can have record in more than one databases, whereas it is belonging to a single person so those records should be merged. Also sometimes a situation may occur where you need entire history of a person in this case record linkage will make it possible. Many Researches has been done for efficiently linking the records as record linking is becoming important day-by-day since it increases the quality of the data. In this research we are going to focus on algorithm for efficiently linking the records and keeping records secure. The software called FEBRL is used for comparing our algorithm efficiency with previously defined algorithms.

References
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  3. Timothy C Heavens,James C. Bezdek,Marimuthu Palsniwami, ”Scalable Single Linkage Heirarchical Clustering for BigData”, University of Melbourne,USA,Australia
  4. Liang Jin, Chen Li,Sharad Mehrotra,” Efficient Record Linkage in Large Datasets”, University of California,Irvine
  5. Rainer Schnell,”An Efficient Privacy Preserving Record Linkage Technique for Administrative data and census”,Statistical Journal of (IAOS),2014
  6. Peter Christen, ”Overview and taxonomy of Techniques for Privacy-preserving Record Linkage ” (JSM) Joint Statistical Meeting, August 2013
  7. Rohan Baxtor ,peter christen, Tim churches, ” A Comparison for Fast Blocking methods for Record Linkage”, Australian National University, Australia
  8. Dimitrios Karapiperis,Aris Gkoulalas-Divanis,Vassilios S.Verykios,”Summarization Algorithms for Record Linkage” Hellenis Open University Patras Greece 2005
Index Terms

Computer Science
Information Sciences

Keywords

Efficient Big data Records Clustering