NDLI: Bridging gaps between several frameworks for the idea of granulation

Content Provider	IEEE Xplore Digital Library
Author	Dubois, D. Prade, H.
Copyright Year	2011
Description	Author affiliation: IRIT, CNRS & Université de Toulouse, 31062 Cedex 09, France (Dubois, D.; Prade, H.)
Abstract	Two important ideas at the core of Zadeh's seminal contributions to fuzzy logic and approximate reasoning are the notions of granulation and of possibilistic uncertainty. In this paper, elaborating on the basis of some formal analogy, recently made by the authors, between possibility theory and formal concept analysis, we suggest other bridges between theories for which the concept of granulation is central. We highlight the common features between the notion of extensional fuzzy set with respect to a similarity relation and the notion of concept. We also discuss the case of fuzzy rough sets. Thus, we point out some fruitful cross-fertilizations between the possibilistic representation of information and several views of granulation emphasizing the idea of clusters of points that can be identified respectively on the basis of their closeness, or of their common labeling in terms of properties.
Starting Page	59
Ending Page	65
File Size	135037
Page Count	7
File Format	PDF
ISBN	9781424499816
e-ISBN	9781424499823
DOI	10.1109/FOCI.2011.5949479
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-11
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Fuzzy sets Possibility theory Uncertainty Rough sets rough set Electronic mail formal concept analysis Equations possibility theory granulation extensional fuzzy set
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Bridging gaps between several forms of granular computing

The entropy for rough fuzzy sets

A Framework for Imprecise Context Reasoning

New links between mathematical morphology and fuzzy property-oriented concept lattices

Knowledge-based fuzzy MLP with rough sets

A novel method of the Rough Interval-valued Intuitionistic Fuzzy Sets

Construct new lattices based on rough set theory

A fuzzy model of rough sets

Fuzziness in Covering Generalized Rough Sets

Bridging gaps between several frameworks for the idea of granulation

Similar Documents

Bridging gaps between several forms of granular computing

The entropy for rough fuzzy sets

A Framework for Imprecise Context Reasoning

New links between mathematical morphology and fuzzy property-oriented concept lattices

Knowledge-based fuzzy MLP with rough sets

A novel method of the Rough Interval-valued Intuitionistic Fuzzy Sets

Construct new lattices based on rough set theory

A fuzzy model of rough sets

Fuzziness in Covering Generalized Rough Sets

Bridging gaps between several frameworks for the idea of granulation