Element matching in concept maps

Authors:
Byron Marshall;Therani Madhusudan
Affiliations:
University of Arizona, Tucson, AZ;University of Arizona, Tucson, AZ
Venue:
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
Year:
2004

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Abstract

Concept maps (CM) are informal, semantic, node-link conceptual graphs used to represent knowledge in a variety of applications. Algorithms that compare concept maps would be useful in supporting educational processes and in leveraging indexed digital collections of concept maps. Map comparison begins with element matching and faces computational challenges arising from vocabulary overlap, informality, and organizational variation. Our implementation of an adapted similarity flooding algorithm improves matching of CM knowledge elements over a simple string matching approach.