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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure

As the amount of data generated is growing exponentially, harnessing such voluminous data has become a major challenge these years especially bibliographic data. This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean...

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Main Authors: Ramasamy, Chitra, Zolkepli, Maslina
Format: Article
Language:English
Published: Institute of Advanced Scientific Research 2019
Online Access:http://psasir.upm.edu.my/id/eprint/79682/1/Enhanced%20anti-mammary%20gland%20cancer%20.pdf
http://psasir.upm.edu.my/id/eprint/79682/
https://www.jardcs.org/abstract.php?id=978
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spelling my.upm.eprints.796822022-10-05T02:08:39Z http://psasir.upm.edu.my/id/eprint/79682/ Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure Ramasamy, Chitra Zolkepli, Maslina As the amount of data generated is growing exponentially, harnessing such voluminous data has become a major challenge these years especially bibliographic data. This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. A steady increase of publications recorded in the Digital Bibliography and Library Project (DBLP) can be identified from year 1936 until 2018, reaching the number 4,327,507 publications. This study will be focusing on the visualization of bibliographic data by retrieving the most influenced papers using hybrid clustering techniques and visualize it in an understandable network diagram using the weight age node. This web based approach will be using Java programming language and Mongo DB (NoSQL database) to improve the retrieval performance by 80%, precision of the search result of the bibliographic data by omitting non-significance papers and visualizing a clearer network diagram using centrality measure for better decision making. This method will make ease for the young researchers, educators and students to dive into the enormous real world social and biological network. Institute of Advanced Scientific Research 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/79682/1/Enhanced%20anti-mammary%20gland%20cancer%20.pdf Ramasamy, Chitra and Zolkepli, Maslina (2019) Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure. Journal of Advanced Research in Dynamical and Control Systems, 11 (3 spec.). pp. 1734-1742. ISSN 1943-023X https://www.jardcs.org/abstract.php?id=978
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description As the amount of data generated is growing exponentially, harnessing such voluminous data has become a major challenge these years especially bibliographic data. This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. A steady increase of publications recorded in the Digital Bibliography and Library Project (DBLP) can be identified from year 1936 until 2018, reaching the number 4,327,507 publications. This study will be focusing on the visualization of bibliographic data by retrieving the most influenced papers using hybrid clustering techniques and visualize it in an understandable network diagram using the weight age node. This web based approach will be using Java programming language and Mongo DB (NoSQL database) to improve the retrieval performance by 80%, precision of the search result of the bibliographic data by omitting non-significance papers and visualizing a clearer network diagram using centrality measure for better decision making. This method will make ease for the young researchers, educators and students to dive into the enormous real world social and biological network.
format Article
author Ramasamy, Chitra
Zolkepli, Maslina
spellingShingle Ramasamy, Chitra
Zolkepli, Maslina
Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
author_facet Ramasamy, Chitra
Zolkepli, Maslina
author_sort Ramasamy, Chitra
title Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
title_short Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
title_full Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
title_fullStr Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
title_full_unstemmed Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
title_sort enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
publisher Institute of Advanced Scientific Research
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/79682/1/Enhanced%20anti-mammary%20gland%20cancer%20.pdf
http://psasir.upm.edu.my/id/eprint/79682/
https://www.jardcs.org/abstract.php?id=978
_version_ 1746211778596962304
score 13.211869

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