Search Results for author: Ge Fan

Found 8 papers, 2 papers with code

MV-HAN: A Hybrid Attentive Networks based Multi-View Learning Model for Large-scale Contents Recommendation

no code implementations14 Oct 2022 Ge Fan, Chaoyun Zhang, Kai Wang, Junyang Chen

In this paper, we introduce a novel Multi-View Approach with Hybrid Attentive Networks (MV-HAN) for contents retrieval at the matching stage of recommender systems.

MULTI-VIEW LEARNING Recommendation Systems +1

QuickSkill: Novice Skill Estimation in Online Multiplayer Games

no code implementations15 Aug 2022 Chaoyun Zhang, Kai Wang, Hao Chen, Ge Fan, Yingjie Li, Lifang Wu, Bingchao Zheng

However, the skill rating of a novice is usually inaccurate, as current matchmaking rating algorithms require considerable amount of games for learning the true skill of a new player.

Fairness

A collaborative filtering model with heterogeneous neural networks for recommender systems

no code implementations27 May 2019 Ge Fan, Wei Zeng, Shan Sun, Biao Geng, Weiyi Wang, Weibo Liu

One advantage of deep neural network is that the performance of the algorithm can be easily enhanced by augmenting the depth of the neural network.

Collaborative Filtering Recommendation Systems +2

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