User recommendation in reciprocal and bipartite social networks -- a case study of online dating

摘要

Many social networks in our daily life are bipartite networks built onreciprocity. How can we recommend users/friends to a user, so that the user isinterested in and attractive to recommended users? In this research, we proposea new collaborative filtering model to improve user recommendations inreciprocal and bipartite social networks. The model considers a user's "taste"in picking others and "attractiveness" in being picked by others. A case studyof an online dating network shows that the new model has good performance inrecommending both initial and reciprocal contacts.