Ning Li

According to our database, Ning Li authored at least 8 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

MiST: Enhancing Traffic Predictions with a Mixing Spatio-temporal Neural Network.

Zhixiang He, Mengzan Gong, Jia-Dong Zhang, Xiliang Liu, Chi-Yin Chow, Ning Li, Xiaoli Sun

Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

2023

Pairwise and Hyper-correlations Based Spatiotemporal Neural Networks for Traffic Speed Predictions.

Zhixiang He, Jia-Dong Zhang, Chi-Yin Chow, Ning Li, Xiliang Liu, Pengfei Lin, Xiaoli Sun

Proceedings of the 24th IEEE International Conference on Mobile Data Management, 2023

2021

Improving Dialog System Grounded with Unstructured Knowledge by Domain Adaptive Pre-Training and Post-Ranking.

Zhi Zeng, Kam-Yiu Lam, Chi-Yin Chow, Ning Li

Int. J. Humanoid Robotics, 2021

DA-BERT: Enhancing Knowledge Selection in Dialog via Domain Adapted BERT with Dynamic Masking Probability.

Zhi Zeng, Chi-Yin Chow, Ning Li

Proceedings of the IEEE International Conference on Smart Computing, 2021

2020

SEML: A Semi-Supervised Multi-Task Learning Framework for Aspect-Based Sentiment Analysis.

Ning Li, Chi-Yin Chow, Jia-Dong Zhang

IEEE Access, 2020

EMOVA: A Semi-supervised End-to-End Moving-Window Attentive Framework for Aspect Mining.

Ning Li, Chi-Yin Chow, Jia-Dong Zhang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

2019

Seeded-BTM: Enabling Biterm Topic Model with Seeds for Product Aspect Mining.

Ning Li, Chi-Yin Chow, Jia-Dong Zhang

Proceedings of the 21st IEEE International Conference on High Performance Computing and Communications; 17th IEEE International Conference on Smart City; 5th IEEE International Conference on Data Science and Systems, 2019

GRADI: Towards Group Recommendation Using Attentive Dual Top-Down and Bottom-Up Influences.

Zhixiang He, Chi-Yin Chow, Jia-Dong Zhang, Ning Li

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019