This article describes a recommender system (RS) in the cultural heritage area, which takes into account the activities on social media performed by the target user and her friends. For this purpose, the system exploits linked open data (LOD) as well. More specifically, the proposed RS (i) extracts information from social networks (e.g., Facebook) by analyzing content generated by users and those included in their social networks; (ii) performs disambiguation tasks through LOD tools; (iii) profiles the user as a social graph; (iv) provides the actual user with personalized suggestions of artistic and cultural resources by integrating collaborative filtering algorithms with semantic technologies for leveraging LOD sources such as DBpedia and Europeana.
|Titolo:||A social cultural recommender based on linked open data|
|Data di pubblicazione:||2017|
|Citazione:||De Angelis, A., Gasparetti, F., Micarelli, A., & Sansonetti, G. (2017). A social cultural recommender based on linked open data. In UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (pp.329-332). Association for Computing Machinery, Inc.|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|