1 Department of Computer Science, Faculty of Science, Aarhus University, Aarhus University2 Department of Computer Science, Science and Technology, Aarhus University3 Department of Computer Science, Science and Technology, Aarhus University
Many machine-learning techniques use feedback information. However, current context fusion systems do not support this because they constrain processing to be structured as acyclic processing. This paper proposes a generalization which enables the use of cyclic processing in context fusion systems. A solution is proposed to the inherent problem of how to avoid uncontrollable looping during cyclic processing. The solution is based on finding cycles using graph-coloring and breaking cycles using time constraints.
Adjunct Proceedings of the Fifth International Conference on Pervasive Computing (pervasive 2007), 2007, p. 41-44
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The Fifth International Conference on Pervasive Computing, 2007