We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
We consider clustering as computation of a structure of proximity relationships within a data set in a feature space or its subspaces. We propose a data structure to represent suc...
With increasing demands for high performance by embedded systems, especially by digital signal processing applications, embedded processors must increase available instruction lev...
Density-based clustering algorithms have recently gained popularity in the data mining field due to their ability to discover arbitrary shaped clusters while preserving spatial pr...
M. Emre Celebi, Y. Alp Aslandogan, Paul R. Bergstr...
distributed shared-memory (SDSM) provides the abstraction necessary to run shared-memory applications on cost-effective parallel platforms such as clusters of workstations. Howeve...