Paper detail

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

preprint2011arXivOpen access

Signal facts

What is known right now

Open access5 authors3 topics

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.