  Fine-grained user profile generation approaches have made it increasingly
feasible to display on a profile page in which topics a user has expertise or
interest. Earlier work on topical user profiling has been directed at enhancing
search and personalization functionality, but making such profiles useful for
human consumption presents new challenges. With this work, we have taken a
first step toward a semantic layout mode for topical user profiles. We have
developed a topical generalization approach which finds coherent groups of
topics and adds labels to them, based on their association with broader topics
in the Wikipedia category graph. A nested layout mode, employing topical
generalization, is compared with a simpler flat layout mode in our user study.
The results indicate that users favor the nested structure over flat profiles,
but tend to overlook the specific topics on the lower level. We propose a third
layout mode to address this issue.
