Deterministic and probabilistic implementation of context

This paper addresses the problem of implementing an abstract context model. First, the abstract context model is represented by a network of situations. Two different implementations for the situation model are then proposed: a deterministic one based on Petri nets and a probabilistic one based on h...

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Bibliographic Details
Main Authors: Brdiczka, O., Reignier, P., Crowley, J.L., Vaufreydaz, D., Maisonnasse, J.
Format: Conference Proceeding
Language:English
Subjects:
Context modeling
Context-aware services
Hidden Markov models
Humans
Knowledge representation
Natural language processing
Pervasive computing
Petri nets
Testing
Ubiquitous computing
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Summary:This paper addresses the problem of implementing an abstract context model. First, the abstract context model is represented by a network of situations. Two different implementations for the situation model are then proposed: a deterministic one based on Petri nets and a probabilistic one based on hidden Markov models. Both implementations are illustrated and applied to real-world problems
DOI:10.1109/PERCOMW.2006.40