About: A method for autonomous data partitioning

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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #90202 A method for autonomous data partitioning
sameAs	A method for autonomous data partitioning
Title	A method for autonomous data partitioning
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2018-09-01
Creator	José C. Príncipe Plamen P. Angelov Xiaowei Gu
status	peer reviewed published
Publisher	Elsevier
abstract	In this paper, we propose a fully autonomous, local-modes-based data partitioning algorithm, which is able to automatically recognize local maxima of the data density from empirical observations and use them as focal points to form shape-free data clouds, i.e. a form of Voronoi tessellation. The method is free from user- and problem- specific parameters and prior assumptions. The proposed algorithm has two versions: i) offline for static data and ii) evolving for streaming data. Numerical results based on benchmark datasets prove the validity of the proposed algorithm and demonstrate its excellent performance and high computational efficiency compared with the state-of-art clustering algorithms.
Is Part Of	Information Sciences https://kar.kent.ac.uk/id/repository
Subject	QA 75 Electronic computers. Computer science
list of authors	https://kar.kent.ac.uk/id/eprint/90202#authors
volume	460-46
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #90202 A method for autonomous data partitioning

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