Collaborative
Case-Based Recommender Systems

Stefano Aguzzoli*, Paolo Avesani, and Paolo Massa

ITC-IRST,
Via Sommarive 18 - Loc. Pant, I-38050 Povo, Trento, Italy
{aguzzoli , avesani ,massa}@irst.itc.it




Abstract. 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, which is capable
of summarizing many recommendations in one suggestion. Our claim is
that recommending one set of goods is different from recommending a
single good many times. 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.
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