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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Aguzzoli, S., Avesani, P., Massa, P. (2002). Collaborative Case-Based Recommender Systems. In: Craw, S., Preece, A. (eds) Advances in Case-Based Reasoning. ECCBR 2002. Lecture Notes in Computer Science(), vol 2416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46119-1_34
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DOI: https://doi.org/10.1007/3-540-46119-1_34
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