Multi-Graph based Multi-Scenario Recommendation in Large-scale Online Video Services
Fan Zhang, Qiuying Peng, Yulin Wu, Pan Zheng, Rong Zeng, Da Lin, Yue Qi · Companion Proceedings of the Web Conference 2022 · 2022
Recently, industrial recommendation services have been boosted by the continual upgrade of deep learning methods. However, they still face de-biasing challenges such as exposure bias and cold-start problem, where circulations of machine learning training on human interaction history leads algorithms to repeatedly suggest exposed items while ignoring less-active ones. Additional problems exist in multi-scenario platforms, e.g. appropriate data fusion from subsidiary scenarios, which we observe could be alleviated through graph structured data integration via message passing.