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With the growing popularity of Social Web applications, more and more userdata is published on the Web everyday. Our research focuses on investigatingways of mining data from such platforms that can be used for modeling users andfor semantically augmenting user profiles. This process can enhance adaptationand personalization in various adaptive Web-based systems. In this paper, wepresent the U-Sem people modeling service, a framework for the semanticenrichment and mining of people's profiles from usage data on the Social Web.We explain the architecture of our people modeling service and describe itsapplication in an adult e-learning context as an example. Versions: Mar 21,10:10, Mar 25, 09:37

U-Sem: Semantic Enrichment, User Modeling and Mining of Usage Data on the Social Web