Chameleon 2: An Improved Graph-Based Clustering Algorithm

0502857 - ÚMG 2019 RIV US eng J - Článek v odborném periodiku
Bartoň, Tomáš - Bruna, T. - Kordík, P.
Chameleon 2: An Improved Graph-Based Clustering Algorithm.
ACM Transactions on Knowledge Discovery from Data. Roč. 13, č. 1 (2019), č. článku 10. ISSN 1556-4681. E-ISSN 1556-472X
Grant CEP: GA MŠMT LO1220
Institucionální podpora: RVO:68378050
Klíčová slova: Cluster analysis * clustering * graph clustering * pattern recognition
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 2.010, rok: 2019

Traditional clustering algorithms fail to produce human-like results when confronted with data of variable density, complex distributions, or in the presence of noise. We propose an improved graph-based clustering algorithm called Chameleon 2, which overcomes several drawbacks of state-of-the-art clustering approaches. We modified the internal cluster quality measure and added an extra step to ensure algorithm robustness. Our results reveal a significant positive impact on the clustering quality measured by Normalized Mutual Information on 32 artificial datasets used in the clustering literature. This significant improvement is also confirmed on real-world datasets.
Trvalý link: http://hdl.handle.net/11104/0294737