Location-aware Deep Collaborative Filtering

This is the implementation of our paper:

Yiwen Zhang, Chunhui Yin, Qilin Wu*, Qiang He and Haibin Zhu. Location-aware Deep Collaborative Filtering for Service Recommendation, IEEE Transactions on Systems, Man, and Cybernetics: Systems. 10.1109/TSMC.2019.2931723, 2019. (SCI)

Developer: Chun-hui Yin

Affiliate: Big Data and Cloud Service Lab, Anhui University

Last updated: 2019/10/05

Please cite our paper if you use our codes. Thanks!

Environment Requirement

This code can be run at following requirement but not limit to:

• python = 3.6.6
• keras = 2.0.9
• pandas = 0.23.4
• numpy = 1.14.0
• scikit-learn = 0.21
• other installation dependencies required above

Example of Usage

>>>python run_rt.py

>>>python run_tp.py

Dataset

• To simulate the real-world situation, we sparse the original matrix at six densities and generate instances for training
• Here we provide the preprocessed real-world dataset WS-Dream (dataset#1)

Note

• Experiments can be run on multi-core CPUs at 6 densities by turning on parallel mode