Zobrazeno 1 - 10 of 18 pro vyhledávání: '"V Shyamala Susan"'
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Akademický článek
PRIVACY PRESERVING DATA MINING USING MULTIPLE OBJECTIVE OPTIMIZATION
Autor: V. Shyamala Susan, T. Christopher
Publikováno v: ICTACT Journal on Soft Computing, Vol 7, Iss 1, Pp 1366-1371 (2016)
Privacy preservation is that the most targeted issue in information publication, because the sensitive data shouldn't be leaked. For this sake, several privacy preservation data mining algorithms are proposed. In this work, feature selection using ev
Externí odkaz: https://doaj.org/article/b563688486494b6fbb49b016c5c9342a
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5
A Novel Network Learning for Image Compressive Sensing
Autor: V. Shyamala Susan, A. P. Bambang Sugiyono
Publikováno v: Sixth International Conference on Intelligent Computing and Applications ISBN: 9789811613340
Most traditional algorithms suffer from intensive computation for compressive sensing image reconstruction. In recent times, algorithms of deep learning-based reconstruction have been proposed to minimize the complexities of time rather than algorith
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::04e16dd0fd46f244f4168f55b93ecc27
https://doi.org/10.1007/978-981-16-1335-7_2
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6
An Anonymization Approach for Dynamic Dataset with Multiple Sensitive Attributes
Autor: V. Shyamala Susan
Publikováno v: Intelligent Computing and Applications ISBN: 9789811555657
In recent days, the personal health information is collected in different fields. When the data is shared for different reasons, it poses a major danger to the field of health care. A number of anonymization methods are implemented to maintain person
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dde696089d1fdbfc582a42cc30f05b24
https://doi.org/10.1007/978-981-15-5566-4_65
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7
PRIVACY PRESERVING DATA MINING USING MULTIPLE OBJECTIVE OPTIMIZATION
Autor: T. Christopher, V. Shyamala Susan
Publikováno v: ICTACT Journal on Soft Computing, Vol 7, Iss 1, Pp 1366-1371 (2016)
Privacy preservation is that the most targeted issue in information publication, because the sensitive data shouldn't be leaked. For this sake, several privacy preservation data mining algorithms are proposed. In this work, feature selection using ev
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d47f0dc61bde588952545f0f843ed8a
http://ictactjournals.in/ArticleDetails.aspx?id=2703
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8
Anonymising the Sparse Dataset: A New Privacy Preservation Approach while Predicting Diseases
Autor: V. Shyamala Susan, T. Christopher
Publikováno v: Indonesian Journal of Electrical Engineering and Informatics, Vol 4, Iss 3 (2016)
Data mining techniques analyze the medical dataset with the intention of enhancing patient’s health and privacy. Most of the existing techniques are properly suited for low dimensional medical dataset. The proposed methodology designs a model for t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doajarticles::1f5387ab1e9054b1ebd2bc1b42eed838
http://section.iaesonline.com/index.php/IJEEI/article/view/229
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10
Advanced Cluster-Based Attribute Slicing: A New Approach for Privacy Preservation
Autor: T. Christopher, V. Shyamala Susan
Publikováno v: Proceedings of the International Conference on Soft Computing Systems ISBN: 9788132226727
Privacy preservation data is an emerging field of research in the data security. Numerous anonymization approaches have been proposed for privacy preservation such as generalization and bucketization. Recent works show that both the techniques are no
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::031dd1ba9fea94bd537cd83f53603971
https://doi.org/10.1007/978-81-322-2674-1_21
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