Integrating user modeling approaches into a framework for recommender agents

DANIELA GODOY; SILVIA SCHIAFFINO; ANALIA AMANDI

INTERNET RESEARCH

EMERALD GROUP PUBLISHING LIMITED

Año: 2010 vol. 20 p. 29 - 54

1066-2243

Despite the various and different domains in which recommender agents are used and the variety of approaches they use to represent user interests and make recommendations, there is some functionality that is common to all of them, such as user model management and recommendation of interesting items. We have generalized these common behaviors into a framework that enables developers to reuse recommender agents? main characteristics in their own developments. Our proposal provides support to the whole recommendation making process: management of different types of user models, memory-based recommendation, model-based recommendation, and social analysis of virtual communities. In addition to the different implementations provided for these components, new algorithms and user model representations can be easily added to our proposed approach. We describe three different recommender agents built by materializing the proposed framework: a movie recommender agent, a tourism recommender agent, and a Web page recommender agent. We also discuss the benefits of our proposal as well as its main limitations.