In this paper, we describe our research activities for integrating the recommendation process of nearby points of artistic and cultural interest (POIs) with related multimedia content. The recommendation engine exploits the potential offered by linked open data (LOD), by following semantic links in the LOD graph to identify movies, books, and music artists/songs related to that specific POI. This content is subsequently reranked based on the activity of the user and her friends on social media (i.e., Facebook), in order to provide personalized suggestions.
Sansonetti, G., Gasparetti, F., Micarelli, A. (2019). Cross-domain recommendation for enhancing cultural heritage experience. In ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization (pp.413-415). Association for Computing Machinery, Inc [10.1145/3314183.3323869].
Cross-domain recommendation for enhancing cultural heritage experience
Sansonetti G.
Membro del Collaboration Group
;Gasparetti F.;Micarelli A.
2019-01-01
Abstract
In this paper, we describe our research activities for integrating the recommendation process of nearby points of artistic and cultural interest (POIs) with related multimedia content. The recommendation engine exploits the potential offered by linked open data (LOD), by following semantic links in the LOD graph to identify movies, books, and music artists/songs related to that specific POI. This content is subsequently reranked based on the activity of the user and her friends on social media (i.e., Facebook), in order to provide personalized suggestions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
