Semantically Segmented Clustering Based on Possibilistic and Rough Set Theories-Reference-Cited by-同舟云学术

Semantically Segmented Clustering Based on Possibilistic and Rough Set Theories

Published:2015-03-28 Issue:6 Volume:30 Page:676-706
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int. J. Intell. Syst.

Author:

Ammar Asma¹,Elouedi Zied¹,Lingras Pawan²

Affiliation:

1. LARODEC; Institut Supérieur de Gestion de Tunis, Université de Tunis; 2000 Le Bardo Tunisia

2. Department of Mathematics and Computing Science; Saint Mary's University; Halifax Nova Scotia B3H 3C3 Canada

Funder

Natural Sciences and Engineering Research Council, Canada

Publisher

Wiley

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/int.21723/fullpdf

Reference51 articles.

1. A new possibilistic clustering method: the possibilistic k-modes. In: Proc 12th Int Confer of the Italian Association for Artificial Intelligence;Ammar;Lect Notes Artif Intell,2011

2. The k-modes method under possibilistic framework;Ammar;Canadian Conf on AI. Lect Notes Artif Intell,2013

3. Selection initial modes for belief k-modes method;Hariz;Int J Appl Sci Eng Technol,2007

4. Iterative meta-clustering through granular hierarchy of supermarket customers and products;Lingras;Inform Sci,2014

5. RPKM: The rough possibilistic k-modes. In: Proc 20th Int Symp on Methodologies for Intelligent Systems; Macau, China, December 4-7, 2012;Ammar;Lect Notes Artif Intell,2012

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