Collaborative Case-Based Recommender Systems

We introduce an application combining CBR and collaborative filtering techniques in the music domain. We describe a scenario in which a new kind of recommendation is required suitable to summarize in one suggestion many recommendations. Our claim is that to recommend a set of goods is different from recommending many times a single good. The paper illustrates how a case-based reasoning approach can provide an effective solution to this problem reducing the drawbacks related to the user profiles. CoCoA, a compilation compiler advisor, will be described as a running example of a collaborative case-based recommendation system