Probabilistic latent clustering of device usage

Abstract

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. © Springer-Verlag Berlin Heidelberg 2005.