An evidence-based approach to handle semantic heterogeneity in interoperable distributed user models

Abstract

Nowadays, the idea of personalization is regarded as crucial in many areas. This requires quick and robust approaches for developing reliable user models. The next generation user models will be distributed (segments of the user model will be stored by different applications) and interoperable (systems will be able to exchange and use user model fractions to enrich user experiences). We propose a new approach to deal with one of the key challenges of interoperable distributed user models - semantic heterogeneity. The paper presents algorithms to automate the user model exchange across applications based on evidential reasoning and advances in the Semantic Web. © 2008 Springer-Verlag Berlin Heidelberg.