Amit Sharma
ABSTRACT
Recommendations are not just informed by the social network, they may also influence it. Thinking about how recommendations impact underlying social processes provides a network-centric approach to recommendation. We describe the design of a recommender system, PopCore, as a testbed for understanding the interplay between recommendation and networks.
- J. Chen, R. Nairn, L. Nelson, M. Bernstein, and E. Chi. Short and tweet: experiments on recommending content from information streams. In Proc. CHI '10. Google Scholar
Digital Library
- A. Sharma and D. Cosley. Network-centric recommendation: Personalization with and in social networks. In Proc. SocialCom '11.Google Scholar
- M. S. Bernstein, A. Marcus, D. R. Karger, and R. C. Miller. Enhancing directed content sharing on the web. In Proc. CHI '10. Google ScholarDigital Library
- I. Guy, N. Zwerdling, D. Carmel, I. Ronen, E. Uziel, S. Yogev, and S. Ofek-Koifman. Personalized recommendation of social software items based on social relations. In Proc. RecSys '09. Google ScholarDigital Library
Index Terms
- PopCore: a system for network-centric recommendation
Recommendations
Recommending Followees Based on Content Weighted User Interest Homophily
ICIMCS'16: Proceedings of the International Conference on Internet Multimedia Computing and ServiceWe study the problem of recommending followees to users on content curation social networks (CCSNs). Different from existing friendship-oriented user recommendation approaches, we exploit user interest homophily to recommend users of similar interests, ...
SFViz: interest-based friends exploration and recommendation in social networks
VINCI '11: Proceedings of the 2011 Visual Information Communication - International SymposiumFriend recommendation is popular in social network services to help people make new friends and expand their networks. Friend recommendation is either based on topological structures of a social network, or derived from profile information of users. ...
User Preference Translation Model for Next Top-k Items Recommendation with Social Relations
Database Systems for Advanced ApplicationsAbstractRecommendation systems are used to predict the interests of users through the analysis of historical preferences. Collaborative filtering-based approaches usually ignore the sequential information and sequential recommendation usually focus on the ...
Comments