The thesis investigates groups of people in a mobile community practicing mobile communication in a context-sensitive way and also interacting in the real world. In this scenario, the concept of an Ad-Hoc-Group as a contextual manifestation or instantiation of an existing social group is of special significance. In view of detecting and modeling of (Ad-Hoc-)groups, several examples for classes of data (location- and velocity-data, natural language interest phrases and hierarchical, text-based communication-data) in mobile communities are investigated. Similarity measures are constructed and verified by empiric means or through stochastic simulation. On this basis, special clustering approaches for the detection and modeling of (Ad-Hoc-)groups are developed and tested. The thesis concludes with a discussion on possible applications for the methods which have been developed.
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The thesis investigates groups of people in a mobile community practicing mobile communication in a context-sensitive way and also interacting in the real world. In this scenario, the concept of an Ad-Hoc-Group as a contextual manifestation or instantiation of an existing social group is of special significance. In view of detecting and modeling of (Ad-Hoc-)groups, several examples for classes of data (location- and velocity-data, natural language interest phrases and hierarchical, text-based co...
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