5 citations · 8 across the 4 of their papers we have counts for
5 papers
Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation
Yongjing Hao, Pengpeng Zhao, Xuefeng Xian +5
Sequential Recommendation aims to predict the next item based on user behaviour. Recently, Self-Supervised Learning (SSL) has been proposed to improve recommendation performance. H…
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks
Jiaan Wang, Beiqi Zou, Zhixu Li +4
Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context. The key challenges of the task lie in…
Graph Factorization Machines for Cross-Domain Recommendation
Dongbo Xi, Fuzhen Zhuang, Yongchun Zhu +3
Recently, graph neural networks (GNNs) have been successfully applied to recommender systems. In recommender systems, the user's feedback behavior on an item is usually the result…
Deep Cross Networks with Aesthetic Preference for Cross-domain Recommendation
Jian Liu, Pengpeng Zhao, Yanchi Liu +5
When purchasing appearance-first products, e.g., clothes, product appearance aesthetics plays an important role in the decision process. Moreover, user's aesthetic preference, whic…
Where to Go Next: A Spatio-temporal LSTM model for Next POI Recommendation
Pengpeng Zhao, Haifeng Zhu, Yanchi Liu +3
Next Point-of-Interest (POI) recommendation is of great value for both location-based service providers and users. Recently Recurrent Neural Networks (RNNs) have been proved to be…