Exploiting preference queries for searching learning resources

Abstract

While the growing number of learning resources increases the choice for learners, it also makes it more and more difficult to find suitable courses. Thus, improved search capabilities on learning resource repositories are required. We propose an approach for learning resource search based on preference queries. A preference query does not only allow for hard constraints (like 'return lectures about Mathematics') but also for soft constraints (such as 'I prefer a course on Monday, but Tuesday is also fine'). Such queries always return the set of optimal items with respect to the given preferences. We show how to exploit this technique for the learning domain, and present the Personal Preference Search Service (PPSS) which offers significantly enhanced search capabilities compared to usual search facilities for learning resources. © Springer-Verlag Berlin Heidelberg 2007.