NDLI: Fuzzy knowledge representation, learning and optimization with Bayesian analysis in fuzzy semantic networks

Content Provider	IEEE Xplore Digital Library
Author	Omri, M.N.
Copyright Year	1999
Description	Author affiliation: Dept. de Math. et d'Inf., Inst. Preparatoire aux Etudes d'Ingenieur, Monastir, France (Omri, M.N.)
Abstract	The paper presents an optimization method, based on both Bayesian analysis technique and Gallois lattice of a fuzzy semantic network. The technical system we use learns by interpreting an unknown word using the links created between this new word and known words. The main link is provided by the context of the query. When a novice's query is confused with an unknown verb (goal) applied to a known noun denoting either an object in the ideal user's network or an object in the user's network, the system infers that this new verb corresponds to one of the unknown goals. With the learning of new words for natural language interpretation, which is produced in agreement with the user, the system improves its representation scheme at each experiment with a new user and in addition, takes advantage of previous discussions with users. The semantic net of user objects thus obtained by these kinds of learning is not always optimal because some relationships between a couple of user objects can be generalized and others suppressed according to values of forces that characterize them. Indeed, to simplify the obtained net, we propose to proceed to an inductive Bayesian analysis on the net obtained from Gallois lattice. The objective of this analysis can be seen as an operation of filtering of the obtained descriptive graph.
Starting Page	412
Ending Page	417
File Size	500150
Page Count	6
File Format	PDF
ISBN	0780358716
DOI	10.1109/ICONIP.1999.844024
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-11-16
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge representation Bayesian methods Lattices Natural languages Fuzzy sets Intelligent networks Optimization methods Filtering Intelligent systems Software standards
Content Type	Text
Resource Type	Article

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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
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