Variational Extensions to EM and Multinomial PCA
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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We investigate an application of Probabilistic Latent Semantics to the problem of device usage analysis in an infrastructure in which multiple users have access to a shared pool of devices delivering different kinds of service and service levels. Each invocation of a service by a user, called a job, is assumed to be logged simply as a co-occurrence of the identifier of the user and that of the device used. The data is best modelled by assuming that multiple latent variables (instead of a single one as in traditional PLSA) satisfying different types of constraints explain the observed variables of a job. We discuss the application of our model to the printing infrastructure in an office environment.