k-means++: the advantages of careful seeding
Arthur, D. & Vassilvitskii, S.
, 'SODA '07: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms', Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1027-1035 (2007)
The structure and function of complex networks
Newman, M. E. J.
Inspired by empirical studies of networked systems such as the Internet,
cial networks, and biological networks, researchers have in recent years
veloped a variety of techniques and models to help us understand or predict
e behavior of these systems. Here we review developments in this field,
cluding such concepts as the small-world effect, degree distributions,
ustering, network correlations, random graph models, models of network growth
d preferential attachment, and dynamical processes taking place on networks.
A New Methodology to Compare Clustering Algorithms
Robardet, C. & Feschet, F.
, 'IDEAL '00: Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents', Springer-Verlag, London, UK, 565-570 (2000)
