14 citations · 38 across the 4 of their papers we have counts for
6 papers
Preference Enhanced Social Influence Modeling for Network-Aware Cascade Prediction
Likang Wu, Hao Wang, Enhong Chen +3
Network-aware cascade size prediction aims to predict the final reposted number of user-generated information via modeling the propagation process in social networks. Estimating th…
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation
Kai Zhang, Hao Qian, Qi Liu +4
Recent studies in recommender systems have managed to achieve significantly improved performance by leveraging reviews for rating prediction. However, despite being extensively stu…
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction
Kai Zhang, Hao Qian, Qing Cui +5
In the Click-Through Rate (CTR) prediction scenario, user's sequential behaviors are well utilized to capture the user interest in the recent literature. However, despite being ext…
Sampling-Decomposable Generative Adversarial Recommender
Binbin Jin, Defu Lian, Zheng Liu +4
Recommendation techniques are important approaches for alleviating information overload. Being often trained on implicit user feedback, many recommenders suffer from the sparsity c…
Deep Technology Tracing for High-tech Companies
Han Wu, Kun Zhang, Guangyi Lv +5
Technological change and innovation are vitally important, especially for high-tech companies. However, factors influencing their future research and development (R&D) trends are b…
Skeptical Deep Learning with Distribution Correction
Mingxiao An, Yongzhou Chen, Qi Liu +4
Recently deep neural networks have been successfully used for various classification tasks, especially for problems with massive perfectly labeled training data. However, it is oft…