U-Sem: Semantic Enrichment, User Modeling and Mining of Usage Data on   the Social Web
  With the growing popularity of Social Web applications, more and more user data is published on the Web everyday. Our research focuses on investigating ways of mining data from such platforms that can be used for modeling users and for semantically augmenting user profiles. This process can enhance adaptation and personalization in various adaptive Web-based systems. In this paper, we present the U-Sem people modeling service, a framework for the semantic enrichment and mining of people's profiles from usage data on the Social Web. We explain the architecture of our people modeling service and describe its application in an adult e-learning context as an example. Versions: Mar 21, 10:10, Mar 25, 09:37 
Fabian Abel, Ilknur Celik, Claudia Hauff, Laura Hollink, Geert-Jan   Houben
cs.IR cs.AI cs.HC