A Novel Algorithm for Matching Conceptual and Related Graphs

This paper presents a new similarity metric and algorithm for situations represented as graphs. The metric is based on the concept of shared information, and there is discussion of how this would apply for different forms of similarity—including surface, structural and thematic similarity. An algorithm is presented which will determine the similarity of two conceptual graphs for any given measure of information content, which can, as a result, be used for any similarity measure that is based on the concept of shared information. It therefore allows the very flexible use of domain and application specific factors. While the algorithm is not polynomial time, it is argued that for real examples of a useful size it can give an answer in a reasonable time.

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