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2000
Springer

Prototype Learning with Attributed Relational Graphs

10 years 7 months ago
Prototype Learning with Attributed Relational Graphs
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.
Pasquale Foggia, Roberto Genna, Mario Vento
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where SSPR
Authors Pasquale Foggia, Roberto Genna, Mario Vento
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