Using category-based collaborative filtering in the Active WebMuseum

Collaborative filtering is an important technology for creating user-adapting Web sites. In general the efforts of improving filtering algorithms and using the predictions for the presentation of filtered objects are decoupled. Therefore, common measures (or metrics) for evaluating collaborative filtering (recommender) systems focus mainly on the prediction algorithm. It is hard to relate the classic measurements to actual user satisfaction because of the way the user interacts with the recommendations, determined by their representation, influences the benefits for the user. We propose an abstract access paradigm, which can be applied to the design of filtering systems, and at the same time formalizes the access to filtering results via multi-corridors (based on content-based categories). This leads to new measures which better relate to the user satisfaction. We use these measures to evaluate the use of various kinds of multi-corridors for our prototype user-adapting Web site, the Active WebMuseum