Fan Mo

According to our database, Fan Mo authored at least 11 papers between 2019 and 2025.

Collaborative distances:

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

2025

Light distillation for Incremental Graph Convolution Collaborative Filtering.

X. Fan, Fan Mo, Chongxian Chen, Hayato Yamana

CoRR, May, 2025

Personalized Fashion Recommendation with Image Attributes and Aesthetics Assessment.

Chongxian Chen, Fan Mo, Xin Fan, Hayato Yamana

CoRR, January, 2025

Synergistic fusion framework: Integrating training and non-training processes for accelerated graph convolution network-based recommendation.

Fan Mo, Xin Fan, Chongxian Chen, Hayato Yamana

Pattern Recognit., 2025

2024

Sampling-based epoch differentiation calibrated graph convolution network for point-of-interest recommendation.

Fan Mo, Xin Fan, Chongxian Chen, Changhao Bai, Hayato Yamana

Neurocomputing, February, 2024

Data-Efficient Massive Tool Retrieval: A Reinforcement Learning Approach for Query-Tool Alignment with Language Models.

Yuxiang Zhang, Xin Fan, Junjie Wang, Chongxian Chen, Fan Mo, Tetsuya Sakai, Hayato Yamana

Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, 2024

2023

EPT-GCN: Edge propagation-based time-aware graph convolution network for POI recommendation.

Fan Mo, Hayato Yamana

Neurocomputing, July, 2023

2022

Decoy Effect of Recommendation Systems on Real E-commerce Websites.

Fan Mo, Tsuneo Matsumoto, Nao Fukushima, Fuyuko Kido, Hayato Yamana

Proceedings of the 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), 2022

GN-GCN: Combining Geographical Neighbor Concept with Graph Convolution Network for POI Recommendation.

Fan Mo, Hayato Yamana

Proceedings of the Information Integration and Web Intelligence, 2022

2021

Real-time Periodic Advertisement Recommendation Optimization under Delivery Constraint using Quantum-inspired Computer.

Fan Mo, Huida Jiao, Shun Morisawa, Makoto Nakamura, Koichi Kimura, Hisanori Fujisawa, Masafumi Ohtsuka, Hayato Yamana

Proceedings of the 23rd International Conference on Enterprise Information Systems, 2021

2020

Real-Time Periodic Advertisement Recommendation Optimization using Ising Machine.

Fan Mo, Huida Jiao, Shun Morisawa, Makoto Nakamura, Koichi Kimura, Hisanori Fujisawa, Masafumi Ohtsuka, Hayato Yamana

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Point of Interest Recommendation by Exploiting Geographical Weighted Center and Categorical Preference.

Fan Mo, Hayato Yamana

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019