  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
