Reasoning Over Knowledge Graph Paths for Recommendation

This is code related to the AAAI 2019 paper "Explainable Reasoning over Knowledge Graphs for Recommendation.". The code  makes extensive use of machine learning techniques, and will be useful for training and prediction of recommendation attributes of media, or other items as described in the paper.

Platform Requirements

This code requires Python(2.7 or 3.5) and Lua(5.3). Please ensure the runtime environments for these are installed. The details could be found in the readMe.pdf.

Steps to Build a Model File in Training Model & Steps to Make Predictions

The model details could be found through readMe.pdf.

Attribution and Acknowledgements

Acknowledgement and thanks to others for open source work used in this project. Code used in this project is available from the following sources.

1. https://github.com/rajarshd/ChainsofReasoning
   Author: Rajarshi Das
   See Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
   Licensed under at least Section D5 of Github Terms of Service..

2. https://github.com/hexiangnan/neural_collaborative_filtering
   Author: Dr. Xiangnan He (http://www.comp.nus.edu.sg/~xiangnan/)
   See Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu and Tat-Seng Chua (2017). Neural Collaborative Filtering. In             Proceedings of WWW '17, Perth, Australia, April 03-07, 2017.
   Licensed under Apache 2.0.

3. https://github.com/hexiangnan/neural_factorization_machine
   Author: Dr. Xiangnan He (http://www.comp.nus.edu.sg/~xiangnan/)
   See Xiangnan He and Tat-Seng Chua (2017). Neural Factorization Machines for Sparse Predictive Analytics. In Proceedings of SIGIR         '17, Shinjuku, Tokyo, Japan, August 07-11, 2017.
   Licensed under at least Section D5 of Github Terms of Service.

4. https://github.com/HKUST-KnowComp/FMG
   See Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks
   Licensed under at least Section D5 of Github Terms of Service.

License

Modifications Copyright 2018 eBay Inc.
Authors/Developers of Modifications: Dingxian, Wang (diwang@ebay.com) and Canran, Xu (canxu@ebay.com)
New code and modifications to code are licensed under the MIT License..  See LICENSE for the license text.