Different Kinds of Comparisons between Fuzzy Conceptual Graphs

In the context of a microbiological application, our study proposes to extend the Conceptual Graph Model in order to allow one: (i) to represent imprecise data and queries that include preferences, by using fuzzy sets (from fuzzy set theory) in concept vertices, in order to describe either an imprecise concept type or an imprecise referent; (ii) to query a conceptual graph that may include imprecise data (factual graph) using a conceptual graph that may include preferences (query graph). This is performed in two steps: firstly by extending the projection operation to fuzzy concepts, secondly by defining a comparison operation characterised by two matching degrees: the possibility degree of matching and the necessity degree of matching between two graphs, and particularly between a query graph and a factual graph.

[1]  Didier Dubois,et al.  Possibility Theory - An Approach to Computerized Processing of Uncertainty , 1988 .

[2]  Marie-Laure Mugnier,et al.  Conceptual Structures: Theory, Tools and Applications , 1998, Lecture Notes in Computer Science.

[3]  Ollivier Haemmerlé,et al.  Representation of weakly structured imprecise data for fuzzy querying , 2003, Fuzzy Sets Syst..

[4]  Henri Prade,et al.  Lipski's approach to incomplete information databases restated and generalized in the setting of Zadeh's possibility theory , 1984, Inf. Syst..

[5]  Bernhard Ganter,et al.  Conceptual Structures: Logical, Linguistic, and Computational Issues , 2000, Lecture Notes in Computer Science.

[6]  Patrick Bosc,et al.  Soft Querying, a New Feature for Database Management Systems , 1994, DEXA.

[7]  P. Buche,et al.  Representation of semi-structured imprecise data for fuzzy querying , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[8]  L. Zadeh.  Fuzzy sets as a basis for a theory of possibility , 1999 .

[9]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[10]  John F. Sowa,et al.  Conceptual Structures: Information Processing in Mind and Machine , 1983 .

[11]  David Genest,et al.  A Platform Allowing Typed Nested Graphs: How CoGITo Became CoGITaNT (Research Note) , 1998, ICCS.

[12]  Ollivier Haemmerlé,et al.  Towards a Unified Querying System of Both Structured and Semi-structured Imprecise Data Using Fuzzy View , 2000, ICCS.

[13]  Didier Dubois,et al.  Tolerant Fuzzy Pattern Matching: An Introduction , 1995 .

[14]  Wenfei Fan,et al.  Keys with Upward Wildcards for XML , 2001, DEXA.

[15]  John F. Sowa,et al.  Conceptual Graphs for Knowledge Representation , 1993, Lecture Notes in Computer Science.

[16]  M. Mugnier,et al.  Représenter des connaissances et raisonner avec des graphes , 1996 .

[17]  Vilas Wuwongse,et al.  Fuzzy Conceptual Graphs , 1993, ICCS.