SocialRT: A Recommendation Method Based On Social Trust

Autor: Xing Xing, Jianyan Luo, Tiansheng Qu, Zhixin Meng, Hanting Chu, Zhichun Jia
Rok vydání: 2019
Předmět:
Zdroj: 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS).
DOI: 10.1109/ddcls.2019.8908972
Popis: With the advent of online social networks, the approach of recommendation based on social network has emerged. However, some recommendation algorithms based on the trust network do not fully mine the information of user's trust relationships. To alleviate such problems, we propose a socialRT method, which is a social recommendation trust method based on joint matrix decomposition. The proposed socialRT method collective factorizes the following relationship matrix and the social trust relationship matrix to obtain the recommendation model. We have conducted experiments on Sina Weibo dataset, the experimental results demonstrate that the proposed recommendation method leads to a substantial increase in recommendation quality.
Databáze: OpenAIRE