A New Algorithm for Error-Tolerant Subgraph Isomorphism Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Error Correcting Graph Matching: On the Influence of the Underlying Cost Function
IEEE Transactions on Pattern Analysis and Machine Intelligence
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Cases as terms: A feature term approach to the structured representation of cases
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Fuzzy conceptual graphs for matching images of natural scenes
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Distance Patterns in Structural Similarity
The Journal of Machine Learning Research
Experience-Based Design of Behaviors in Videogames
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Towards Case-Based Support for e-Science Workflow Generation by Mining Provenance
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
An Algebraic Framework for Schema Matching
Informatica
Diagnosing and Measuring Incompatibilities between Pairs of Services
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
A Semantic Similarity Measure for Ontology-Based Information
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
A graph matching method and a graph matching distance based on subgraph assignments
Pattern Recognition Letters
Graph based shapes representation and recognition
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Constraint-based graph matching
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Proceedings of the 1st International Conference on Intelligent Semantic Web-Services and Applications
Classification of multi-structured documents: a comparison based on media image
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
A new similarity measure in formal concept analysis for case-based reasoning
Expert Systems with Applications: An International Journal
Design pattern mining using greedy algorithm for multi-labelled graphs
International Journal of Information and Communication Technology
Multi-labeled graph matching: an algorithm model for schema matching
ASIAN'05 Proceedings of the 10th Asian Computing Science conference on Advances in computer science: data management on the web
Ant algorithm for the graph matching problem
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Case-Based student modeling using concept maps
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Reactive tabu search for measuring graph similarity
GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition
A comparative study of ant colony optimization and reactive search for graph matching problems
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Similarity-Based Retrieval With Structure-Sensitive Sparse Binary Distributed Representations
Computational Intelligence
A new case-based classification using incremental concept lattice knowledge
Data & Knowledge Engineering
On the subgraph epimorphism problem
Discrete Applied Mathematics
Similarity assessment and efficient retrieval of semantic workflows
Information Systems
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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.