Grammatical Inference: Introduction and Survey-Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special memorial issue for Professor King-Sun Fu
Algorithms for clustering data
Algorithms for clustering data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation of Normalized Edit Distance and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering of sequences using minimum grammar compexity criterion
ICG! '96 Proceedings of the 3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences
A Minimum Code Length Technique for Clustering of Syntactic Patterns
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
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This paper addresses the problem of structural clustering of string patterns. Adopting the grammar formalism for representing both individual sequences and sets of patterns, a partitional clustering algorithm is proposed. The performance of the new algorithm, taking as reference the corresponding hierarchical version, is analyzed in terms of computational complexity and data partitioning results. The new algorithm introduces great improvements in terms of computational efficiency, as demonstrated by theoretical analysis. Unlike the hierarchical approach, clustering results are dependent on the order of patterns' presentation, which may lead to performance degradation. This effect, however, is overcome by adopting a resampling technique. Empirical evaluation of the methods is performed through application examples, by matching clusters between pairs of partitions and determining an index of clusters agreement.