A New Algorithm for Error-Tolerant Subgraph Isomorphism Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Learning Logical Definitions from Relations
Machine Learning
Prototyping Structural Descriptions: An Inductive Learning Approach
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Performance Evaluation of the VF Graph Matching Algorithm
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
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An algorithm for learning structural patterns given in terms of Attributed Relational Graphs (ARG's) is presented. The algorithm, based on inductive learning methodologies, produces general and coherent prototypes in terms of Generalized Attributed Relational Graphs (GARG's), which can be easily interpreted and manipulated. The learning process is defined in terms of inference operations especially devised for ARG's, as graph generalization and graph specialization, making so possible the reduction of both the computational cost and the memory requirement of the learning process. Experimental results are presented and discussed with reference to a structural method for recognizing characters extracted from ETL database.