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Measuring the similarity of labeled graphs. (English) Zbl 1045.68667

Ashley, Kevin D. (ed.) et al., Case-based reasoning research and development. 5th international conference on case-based reasoning, ICCBR 2003, Trondheim, Norway, June 23–26, 2003. Proceedings. Berlin: Springer (ISBN 3-540-40433-3/pbk). Lect. Notes Comput. Sci. 2689, 80-95 (2003).
Summary: This paper proposes a similarity measure to compare cases represented by labeled graphs. We first define an expressive model of directed labeled graph, allowing multiple labels on vertices and edges. Then we define the similarity problem as the search of a best mapping, where a mapping is a correspondence between vertices of the graphs. A key point of our approach is that this mapping does not have to be univalent, so that a vertex in a graph may be associated with several vertices of the other graph. Another key point is that the quality of the mapping is determined by generic functions, which can be tuned in order to implement domain-dependant knowledge. We discuss some computational issues related to this problem, and we describe a greedy algorithm for it. Finally, we show that our approach provides not only a quantitative measure of the similarity, but also qualitative information which can prove valuable in the adaptation phase of CBR.
For the entire collection see [Zbl 1031.68647].

MSC:

68U99 Computing methodologies and applications
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
68R10 Graph theory (including graph drawing) in computer science
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