NDLI: Learning fuzzy relational descriptions using the logical framework and rough set theory

Content Provider	IEEE Xplore Digital Library
Author	Martienne, E. Quafafou, M.
Copyright Year	1998
Description	Author affiliation: Inst. de Recherche en Inf. de Nantes, France (Martienne, E.)
Abstract	Handling numerical features is quite an open problem for the symbolic approach to machine learning. Indeed, many systems have a limited applicability because of their inability to deal with numerical data. In this paper, we propose an approach for learning definitions of concepts from their examples, in the presence of numerical but also uncertain data. This approach fits in a first order logic framework and its main characteristics are: (1) the use of fuzzy sets to represent numerical data and model uncertain features, and (2) an inductive learning process based on rough set theory which is capable of handling uncertainty within the learning data. Compared to classical symbolic approaches to inductive learning, it differs in two main points: firstly, it becomes possible to represent both sharp and flexible concepts, and secondly the definitions of concepts that are learned are not deterministic but fuzzy. This approach has been implemented through the EAGLE system and evaluated on a real-world problem of organic chemistry. The results obtained show its good potentialities.
Starting Page	939
Ending Page	944
File Size	728243
Page Count	6
File Format	PDF
ISBN	078034863X
ISSN	10987584
DOI	10.1109/FUZZY.1998.686244
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-05-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Fuzzy set theory Set theory Machine learning Fuzzy sets Logic programming Fuzzy systems Uncertainty Numerical models Chemistry
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Theoretical Computer Science Software

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