Schema Evolution publication categorizer

Large information repositories as digital libraries, online shops, etc.
rely on a taxonomy of the objects under consideration to structure the vast contents
and facilitate browsing and searching (e.g., ACM topic classification for
computer science literature, Amazon product taxonomy, etc.). As in heterogenous
communities users typically will use different parts of such an ontology
with varying intensity, customization and personalization of the ontologies is desirable.
Of particular interest for supporting users during the personalization are
collaborative filtering systems which can produce personal recommendations by
computing the similarity between own preferences and the one of other people. In
this paper we adapt a collaborative filtering recommender system to assist users in
the management and evolution of their personal ontology by providing detailed
suggestions of ontology changes. Such a system has been implemented in the
context of Bibster, a peer-to-peer based personal bibliography management tool.
Finally, we report on an experiment with the Bibster community that shows the
performance improvements over non-personalized recommendations.