This paper presents a unifying framework to model casebased reasoning recommender systems (CBR-RS). CBR recommender systems have complex architectures and specialize the CBR problem solving methodology in a number of ways. The goal of the framework is to illustrate with an integrate view the richness of such a general reasoning methodology. The framework was derived by the analysis of seven systems comprising ten different recommender functionalities. The ultimate goal of the proposed framework is to ease the evaluation and the comparison of case-based reasoning recommender systems and provide a tool to identify missing open area for further research
Case-Based Recommender Systems: a Unifying View
Lorenzi, Fabiana;Ricci, Francesco
2004-01-01
Abstract
This paper presents a unifying framework to model casebased reasoning recommender systems (CBR-RS). CBR recommender systems have complex architectures and specialize the CBR problem solving methodology in a number of ways. The goal of the framework is to illustrate with an integrate view the richness of such a general reasoning methodology. The framework was derived by the analysis of seven systems comprising ten different recommender functionalities. The ultimate goal of the proposed framework is to ease the evaluation and the comparison of case-based reasoning recommender systems and provide a tool to identify missing open area for further researchI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
