inContext will develop a novel scientific approach focused on a new blend of human collaboration and service-oriented systems that explores two basic research strands:

  1. efficient and effective support for human interactions and collaboration in various teams through dynamically aggregated software services;
  2. use of human-to-human or human-to-service interactions in applying intelligent mining and learning algorithms that can detect interaction patterns for pro-active service aggregation.

In addressing these issues, inContext will explore novel techniques and algorithms for mining human activities and providing context-relevant services, at the right time and granularity, to human interaction partners in those various team forms. To this end, relevance-based context representation models and autonomic service adaptation methods for context-coupling and enrichment will be developed.


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