Аннотация
This paper applies subgroup discovery for obtaining interesting descriptive
patterns in ubiquitous data. Furthermore, we provide a novel graph-based
analysis approach for assessing the relations between the obtained
subgroup set, and for ranking subgroups according to their relationships
to other subgroups. We present and discuss first results utilizing
real-world data, given by noise measurements with associated subjective
perceptions and a set of tags describing the semantic context.
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