We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
Each clustering algorithm induces a similarity between given data points, according to the underlying clustering criteria. Given the large number of available clustering technique...
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
Clusters of workstations have emerged as an important platform for building cost-effective, scalable, and highlyavailable computers. Although many hardware solutions are available...
Eitan Frachtenberg, Fabrizio Petrini, Juan Fern&aa...