Searching for Temporal Patterns in AmI Sensor Data
Résumé
Data streams emanating from sensors in AmI scenarios often exhibit interesting temporal patterns that point to semantically meaningful events. In this paper we explore two methodologies to uncover this hidden temporal structure: compression-based pattern extractors utilize temporal ordering whereas T-patterns attempt to include estimates for the inter-event times. We suggest improvements to simplify the statistical underpinnings of T-patterns and discuss the relative merits of both methodologies in the light of a number of simulation experiments.
Origine | Fichiers produits par l'(les) auteur(s) |
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