Point of Interest Recommendation by Exploiting Geographical Weighted Center and Categorical Preference. - Fan Mo 002; Hayato Yamana (ICDM Workshops, 2019)

Real-Time Periodic Advertisement Recommendation Optimization using Ising Machine. - Fan Mo 002; Huida Jiao; Shun Morisawa; Makoto Nakamura; Koichi Kimura; Hisanori Fujisawa; Masafumi Ohtsuka; Hayato Yamana (IEEE BigData, 2020)

Real-time Periodic Advertisement Recommendation Optimization under Delivery Constraint using Quantum-inspired Computer. - Fan Mo 002; Huida Jiao; Shun Morisawa; Makoto Nakamura; Koichi Kimura; Hisanori Fujisawa; Masafumi Ohtsuka; Hayato Yamana (ICEIS (1), 2021)

GN-GCN: Combining Geographical Neighbor Concept with Graph Convolution Network for POI Recommendation. - Fan Mo 002; Hayato Yamana (iiWAS, 2022)

Decoy Effect of Recommendation Systems on Real E-commerce Websites. - Fan Mo 002; Tsuneo Matsumoto; Nao Fukushima; Fuyuko Kido; Hayato Yamana (IntRS@RecSys, 2022)

EPT-GCN: Edge propagation-based time-aware graph convolution network for POI recommendation. - Fan Mo 002; Hayato Yamana (Neurocomputing, 2023)

Data-Efficient Massive Tool Retrieval: A Reinforcement Learning Approach for Query-Tool Alignment with Language Models. - Yuxiang Zhang; Xin Fan; Junjie Wang 011; Chongxian Chen; Fan Mo 002; Tetsuya Sakai; Hayato Yamana (SIGIR-AP, 2024)

Sampling-based epoch differentiation calibrated graph convolution network for point-of-interest recommendation. - Fan Mo 002; Xin Fan; Chongxian Chen; Changhao Bai; Hayato Yamana (Neurocomputing, 2024)

Synergistic fusion framework: Integrating training and non-training processes for accelerated graph convolution network-based recommendation. - Fan Mo 002; Xin Fan; Chongxian Chen; Hayato Yamana (Pattern Recognit., 2025)

Personalized Fashion Recommendation with Image Attributes and Aesthetics Assessment. - Chongxian Chen; Fan Mo 002; Xin Fan; Hayato Yamana (CoRR, 2025)

Light distillation for Incremental Graph Convolution Collaborative Filtering. - X. Fan; Fan Mo 002; Chongxian Chen; Hayato Yamana (CoRR, 2025)