We introduce an application combining CBR and collaborative filtering techniques in the music domain. We describe a scenario in which the classical collaborative filtering recommendation algorithm suffers from serious drawbacks: this scenario stresses the difference between a single-interaction case and a dynamically growing user profile. We set up a framework meant to extend collaborative filtering for compositional recommendation systems where cases does not explicitly yield the amount of overlapping items needed by classical filtering

Compositional CBR via Collaborative Filtering

Avesani, Paolo;Massa, Paolo
2001-01-01

Abstract

We introduce an application combining CBR and collaborative filtering techniques in the music domain. We describe a scenario in which the classical collaborative filtering recommendation algorithm suffers from serious drawbacks: this scenario stresses the difference between a single-interaction case and a dynamically growing user profile. We set up a framework meant to extend collaborative filtering for compositional recommendation systems where cases does not explicitly yield the amount of overlapping items needed by classical filtering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/372
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