Personalized Recommendation of Research Papers by Fusing Recommendations from Explicit and Implicit Social Network

Shaikhah Alotaibi, Julita Vassileva
2016 User Modeling, Adaptation, and Personalization  
Combining social network information with collaborative filtering recommendation algorithms has helped to alleviate some drawbacks of collaborative filtering, for example, the cold start problem, and has increased the accuracy of recommendations. However, the user coverage of recommendation for social-based recommendation is low as there is often insufficient data about explicit social relationships among users. In this paper, we fuse recommendation that uses explicit social relations (friends
more » ... nd co-authors) with recommendations that use implicit social relations aiming to increase the user coverage with minimum recommendation accuracy loss. We found that fusing recommendations from friends with recommendations using implicit social networks increases both accuracy and user recommendation coverage while fusing recommendation from co-authors increase the coverage.
dblp:conf/um/AlotaibiV16a fatcat:4chvp5ctazdutii33sjciaqst4