Integrating a Content-based Recommender System into Digital Libraries for Cultural Heritage

Throughout the last decade, the area of Digital Libraries (DL) get more and more interest from both the research and development communities. Likewise, since the release of new platforms enriches them with new features and makes DL more powerful and effective, the number of web sites integrating these kind of tools is rapidly growing. In this paper we propose an approach for the exploitation of digital libraries for personalization goal in cultural heritage scenario. Specifically, we tried to integrate FIRSt (Folksonomy-based Item Recommender syStem), a content-based recommender system developed at the University of Bari, and Fedora, a flexible digital library architecture, in a framework for the adaptive fruition of cultural heritage implemented within the activities of the CHAT research project. In this scenario, the role of the digital library was to store information (such as textual and multimedial ones) about paintings gathered from the Vatican Picture Gallery and to provide them in a multimodal and personalized way through a PDA device given to a user before her visit in a museum. This paper describes the system architecture of our recommender system and its integration in the framework implemented for the CHAT project, showing how this recommendation model has been applied to recommend the artworks located at the Vatican Picture Gallery (Pinacoteca Vaticana), providing users with a personalized museum tour tailored on their tastes. The experimental evaluation we performed also confirmed that these recommendation services are really able to catch the real user preferences thus improving their experience in cultural heritage fruition.