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The MST-KNN with paracliques

Ahmed Shamsul Arefin , Carlos Riveros , Regina Berretta , Pablo Moscato

pp. 373-386

In this work, we incorporate new edges from a paraclique-identification approach to the output of the MST-kNN graph partitioning method. We present a statistical analysis of the results on a dataset originated from a computational linguistic study of 84 Indo-European languages. We also present results from a computational stylistic study of 168 plays of the Shakespearean era. For the latter, results of the Kruskal-Wallis test 1 (observed vs. all permutations) showed a p-value of a 1.62E-11 and a Wilcoxon test a p-value of 8.1E-12. Overall, our results clearly show in both cases that the modified approach provides statistically more significant results than the use of the MST-kNN alone, thus providing a highly-scalable alternative and statistically sound approach for data clustering.

Publication details

DOI: 10.1007/978-3-319-14803-8_29

Full citation:

Shamsul Arefin, A. , Riveros, C. , Berretta, R. , Moscato, P. (2015)., The MST-KNN with paracliques, in M. Randall (ed.), Artificial life and computational intelligence, Dordrecht, Springer, pp. 373-386.

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