Data integration and data privacy through �Pay-As-You-Go� approach

Data Analytics has taken important and demanding problems in the research areas such as computer science, biology, medicine, finance, and homeland security. This research paper has resolved the problem of Entity resolution(ER) which recognizes the database records, which referred to the same real-wo...

Full description

Saved in:
Bibliographic Details
Main Authors: Lydia E.L., Pandiselvam R., Saranya R., Kirutikaa U.S., Ilayaraja M., Shankar K., Maseleno A.
Other Authors: 57196059278
Format: Article
Published: Research Trend 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-24974
record_format dspace
spelling my.uniten.dspace-249742023-05-29T15:29:41Z Data integration and data privacy through �Pay-As-You-Go� approach Lydia E.L. Pandiselvam R. Saranya R. Kirutikaa U.S. Ilayaraja M. Shankar K. Maseleno A. 57196059278 57196346443 57212525827 57210203124 55662288300 56884031900 55354910900 Data Analytics has taken important and demanding problems in the research areas such as computer science, biology, medicine, finance, and homeland security. This research paper has resolved the problem of Entity resolution(ER) which recognizes the database records, which referred to the same real-world entity. The latest explosion of data made ER a impeach problem in a large range of applications. This paper proposed a scalable ER approach, used on-board datasets. Our latest approaches are simple because they consider either the entire ER process or the function, which are matching, and merging records as a black box procedure and used in a large range of ER applications. Pay-as-you-go approach for ER was a limit on the resources (e.g., work, runtime). This made the maximum progress as possible as required. This paper suggests scalable ER methods and new ER functionalities that have been not studied in the previous. Entity Resolution as a black-box operation provides general mechanisms which be used across applications. Further, the issue of managing information leakage, where one must try to avoid important bits of data from resolved by Entity Resolution, to sage against the loss of data privacy. As more of our sensitive data gets unprotected to various merchants, health care providers, employers, social sites and so on, there is a large chance that an adversary can "connect the dots" and piece together our data, which leads to even more damage of privacy. Thus to measure the quantifying data leakage, we use "disinformation" as a device which containing data leakage. � 2019, Research Trend. All rights reserved. Final 2023-05-29T07:29:40Z 2023-05-29T07:29:40Z 2019 Article 2-s2.0-85070650406 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070650406&partnerID=40&md5=3f7beecd5dd378fa4cc92a11536d5cfa https://irepository.uniten.edu.my/handle/123456789/24974 10 2 167 173 Research Trend Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Data Analytics has taken important and demanding problems in the research areas such as computer science, biology, medicine, finance, and homeland security. This research paper has resolved the problem of Entity resolution(ER) which recognizes the database records, which referred to the same real-world entity. The latest explosion of data made ER a impeach problem in a large range of applications. This paper proposed a scalable ER approach, used on-board datasets. Our latest approaches are simple because they consider either the entire ER process or the function, which are matching, and merging records as a black box procedure and used in a large range of ER applications. Pay-as-you-go approach for ER was a limit on the resources (e.g., work, runtime). This made the maximum progress as possible as required. This paper suggests scalable ER methods and new ER functionalities that have been not studied in the previous. Entity Resolution as a black-box operation provides general mechanisms which be used across applications. Further, the issue of managing information leakage, where one must try to avoid important bits of data from resolved by Entity Resolution, to sage against the loss of data privacy. As more of our sensitive data gets unprotected to various merchants, health care providers, employers, social sites and so on, there is a large chance that an adversary can "connect the dots" and piece together our data, which leads to even more damage of privacy. Thus to measure the quantifying data leakage, we use "disinformation" as a device which containing data leakage. � 2019, Research Trend. All rights reserved.
author2 57196059278
author_facet 57196059278
Lydia E.L.
Pandiselvam R.
Saranya R.
Kirutikaa U.S.
Ilayaraja M.
Shankar K.
Maseleno A.
format Article
author Lydia E.L.
Pandiselvam R.
Saranya R.
Kirutikaa U.S.
Ilayaraja M.
Shankar K.
Maseleno A.
spellingShingle Lydia E.L.
Pandiselvam R.
Saranya R.
Kirutikaa U.S.
Ilayaraja M.
Shankar K.
Maseleno A.
Data integration and data privacy through �Pay-As-You-Go� approach
author_sort Lydia E.L.
title Data integration and data privacy through �Pay-As-You-Go� approach
title_short Data integration and data privacy through �Pay-As-You-Go� approach
title_full Data integration and data privacy through �Pay-As-You-Go� approach
title_fullStr Data integration and data privacy through �Pay-As-You-Go� approach
title_full_unstemmed Data integration and data privacy through �Pay-As-You-Go� approach
title_sort data integration and data privacy through �pay-as-you-go� approach
publisher Research Trend
publishDate 2023
_version_ 1806428007631421440
score 13.211869