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Erschienen in:
2015 | OriginalPaper | Buchkapitel
The MST-kNN with Paracliques
verfasst von : Ahmed Shamsul Arefin, Carlos Riveros, Regina Berretta, Pablo Moscato
Erschienen in: Artificial Life and Computational Intelligence
Verlag: Springer International Publishing
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In this work, we incorporate new edges from a paraclique-identification approach to the output of the MST-
k
NN 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-
k
NN alone, thus providing a highly-scalable alternative and statistically sound approach for data clustering.