Analysis of a multi-domain recommender system

Recommending items in a multi-domain environment are more challenging than that in a single-domain one. In this paper, we report our findings on uncovering the association between user´s interests of items across domains that are related to each other to a certain degree using two datasets collected from users with different cultural background. Results lead us to believe that due to cultural influences, user preferences over Western and Eastern items (both entertaining item and entertainer) are significantly different. In addition, results suggest the value of the cross-domain RS and reveal that cross-domain recommendation is sensitive to genre among certain domains (Book, Game and Movie), which is valuable for the algorithmic design and implementation of the RS. The results are valuable for the algorithmic design and implementation of the cross-domain RS targeting at users from different countries. Another most significant potential of cross-domain RS is its ability to exploit users´ versatile interest on items in different domains to make serendipity and novel recommendations especially in large-scale commercial systems.