Closely related to the concept of Machine Learning, Pattern Recognition is the assignment of an output value, termed a label, to a given input value, termed an instance. This is achieved through the application of an algorithm, which usually falls into one of two general categories (although mixed techniques are beginning to be developed): supervised (requires a training set), and unsupervised,...

Cím: Performance comparison of query-based techniques for anti-pattern detection

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This paper is concerned with the inexact matching of attributed, relational graphs for structural pattern recognition. The matching procedure is based on a state space search utilizing heuristic information. Some experimental results are reported.

Pattern recognition stems from the need for automated machine recognition of objects, signals or images, or the need for automated decision-making based on a given set of parameters. Despite over half a century of productive research, pattern recognition continues to be an active area of research because of many unsolved fundamental theoretical problems as well as a rapidly increasing number of...

Properties of shapes and shape patterns are investigated in order to represent shape pattern knowledge for supporting shape pattern recognition. It is based on the notion that shape patterns are classified in terms of similarity of spatial relationships as well as physical properties. Methods for shape pattern recognition are explained and examples from an implementation are presented.