Neural Social Collaborative Ranking

This is our Tensorflow implementation for the paper:

Xiang Wang, Xiangnan He, Liqiang Nie, and Tat-Seng Chua (2019). Item Silk Road: Recommending Items from Information Domains to Social Users. In SIGIR ’17, Shinjuku, Tokyo, Japan, August 07-11, 2017.

Author: Dr. Xiang Wang (xiangwang at u.nus.edu)

Introduction

Neural Social Collaborative Ranking (NSCR) is a new recommendation framework which seamlessly sews up the user-item interactions in the recommendation scenarios and user-user connections in social networks, in order to recommend items to potential social users.

Citation

If you want to use our codes in your research, please cite:

@inproceedings{NSCR17,
  author    = {Xiang Wang and
               Xiangnan He and
               Liqiang Nie and
               Tat{-}Seng Chua},
  title     = {Item Silk Road: Recommending Items from Information Domains to Social
               Users},
  booktitle = {{SIGIR}},
  pages     = {185--194},
  year      = {2017},
}