A Context Prediction Code and Data Base


Many of the currently available sensors do not provide simple, numerical values but more complex data like a list of other devices in range. Although these sensors can, in the general case, not be transformed to numerical values, they nonetheless provide valuable information about the device or user context. For exploiting all available context information, it is thus important to also regard ordinal and nominal sensor values. In this paper, we propose to jointly develop a meta data format for the evaluation and assessment of context recognition and prediction methods.

Proceedings of the Benchmarks and a Database for Context Recognition Workshop