Case-based recommender system inspired by social insects

Fabiana LorenziDaniela Scherer dos SantosAna L. C. Bazzan

Case-based recommender systems can learn about user preferences over time and automatically suggest products that fit these preferences. In this paper we present such a system, called CASIS. In CASIS we combined casebased reasoning approach with a metaphor from colonies of social insects, namely the honey bee dance. In nature, this metaphor is used to indicate the best nectar source among honey bees. Similarly we use it to retrieve the most similar case to the user's query. Our results show that this combination is effective when used in the retrieval step of the recommendation cycle: the most similar case is found by the ìbeesî.

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