# kprn

**Repository Path**: mirrors/kprn

## Basic Information

- **Project Name**: kprn
- **Description**: KPRN 由 eBay 开源，是一个知识图谱路径的推荐模型（Reasoning Over Knowledge Graph Paths for Recommendation）
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 13
- **Forks**: 0
- **Created**: 2019-05-08
- **Last Updated**: 2026-02-28

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Reasoning Over Knowledge Graph Paths for Recommendation
This is code related to the AAAI 2019 paper ["Explainable Reasoning over Knowledge Graphs for Recommendation."](https://arxiv.org/pdf/1811.04540.pdf). 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 <BR>
Author: Rajarshi Das <BR>
See [Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks](https://arxiv.org/abs/1607.01426) <BR>
Licensed under at least [Section D5 of Github Terms of Service.](https://help.github.com/articles/github-terms-of-service/#d-user-generated-content).

2. https://github.com/hexiangnan/neural_collaborative_filtering <BR>
Author: Dr. Xiangnan He (http://www.comp.nus.edu.sg/~xiangnan/) <BR>
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. <BR>
Licensed under [Apache 2.0.](https://github.com/hexiangnan/neural_collaborative_filtering/blob/master/LICENSE)
    
3. https://github.com/hexiangnan/neural_factorization_machine <BR>
Author: Dr. Xiangnan He (http://www.comp.nus.edu.sg/~xiangnan/) <BR>
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. <BR>
Licensed under at least [Section D5 of Github Terms of Service.](https://help.github.com/articles/github-terms-of-service/#d-user-generated-content)
    
4. https://github.com/HKUST-KnowComp/FMG <BR>
See [Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks](http://www.cse.ust.hk/~hzhaoaf/data/kdd17-paper.pdf) <BR>
Licensed under at least [Section D5 of Github Terms of Service.](https://help.github.com/articles/github-terms-of-service/#d-user-generated-content)
    
# License
Modifications Copyright 2018 eBay Inc.<BR>
Authors/Developers of Modifications: Dingxian, Wang (diwang@ebay.com) and Canran, Xu (canxu@ebay.com) <BR> 
New code and modifications to code are licensed under the [MIT License.](https://opensource.org/licenses/MIT).  See LICENSE for the license text.