Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Conceptual graph matching: a flexible algorithm and experiments
Journal of Experimental & Theoretical Artificial Intelligence - Special issue: conceptual graphs workshop
An Exploration into Semantic Distance
Proceedings of the 7th Annual Workshop on Conceptual Structures: Theory and Implementation
Constraint Processing
Multi-label classification and extracting predicted class hierarchies
Pattern Recognition
A conceptual graph based approach for mappings among multiple fuzzy ontologies
Journal of Web Engineering
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This paper presents a combinatorial, structure based approach to the problem of finding a (di)similarity measure between two Conceptual Graphs. With a growing number of ontologies and an increasing need for quick, on the fly knowledge integration and querying, ontology similarity measures are essential for building the foundations of the Semantic Web. Conceptual Graphs benefit from a graph based representation that can be exploited in versatile optimisation techniques. We propose a disimilarity measure based on the content and the structure of two graphs. This disimilarity measure is based on the clique number of the matching graph, a combinatorial structure which encodes the two graphs projection information.