Integrated Recommendation for Public Cultural Service

Recent years recommender systems have been used in the public cultural services to provide personalized services. The single recommendation methods only cover the limited areas of interest of users. To address this issue, this paper proposes an integrated recommender system for cross-domain heterogeneous recommendations of the public cultural resources. The proposed system works on the recommendations for resource, knowledge, semantic tags, and user interest. Using the proposed system, users can explore interesting information in different point of views. Additionally, the proposed system visualizes the recommendation results in suitable ways.