Friend Recall in Online Games via Pre-training Edge Transformers

02/20/2023
by   Liang Yao, et al.
0

Friend recall is an important way to improve Daily Active Users (DAU) in Tencent games. Traditional friend recall methods focus on rules like friend intimacy or training a classifier for predicting lost players' return probability, but ignore feature information of (active) players and historical friend recall events. In this work, we treat friend recall as a link prediction problem and explore several link prediction methods which can use features of both active and lost players, as well as historical events. Furthermore, we propose a novel Edge Transformer model and pre-train the model via masked auto-encoders. Our method achieves state-of-the-art results in the offline experiments and online A/B Tests of three Tencent games.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset