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A tensorflow implementation of Knowledge Graph Convolutional Networks
| Date | Stars |
|---|---|
| 2026-08-04 | 526 |
| 2026-08-06 | 526 |
| 2026-08-13 | 525 |
| 2026-08-18 | 524 |
| 2026-10-10 | 523 |
| 2026-11-04 | 523 |
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# KGCN
This repository is the implementation of [KGCN](https://dl.acm.org/citation.cfm?id=3313417) ([arXiv](https://arxiv.org/abs/1904.12575)):
> Knowledge Graph Convolutional Networks for Recommender Systems
Hongwei Wang, Miao Zhao, Xing Xie, Wenjie Li, Minyi Guo.
In Proceedings of The 2019 Web Conference (WWW 2019)
KGCN is **K**nowledge **G**raph **C**onvolutional **N**etworks for recommender systems, which uses the technique of graph convolutional networks (GCN) to proces knowledge graphs for the purpose of recommendation.
### Files in the folder
- `data/`
- `movie/`
- `item_index2entity_id.txt`: the mapping from item indices in the raw rating file to entity IDs in the KG;
- `kg.txt`: knowledge graph file;
- `music/`
- `item_index2entity_id.txt`: the mapping from item indices in the raw rating file to entity IDs in the KG;
- `kg.txt`: knowledge graph file;
- `user_artists.dat`: raw rating file of Last.FM;
- `src/`: implementations of KGCN.
### Running the code
- Movie
(The raw rating file of MovieLens-20M is too large to be contained in this repository.
Download the dataset first.)
```
$ wget http://files.grouplens.org/datasets/movielens/ml-20m.zip
$ unzip ml-20m.zip
$ mv ml-20m/ratings.csv data/movie/
$ cd src
$ python preprocess.py -d movie
```
- Music
- ```
$ cd src
$ python preprocess.py -d music
```
- open `src/main.py` file;
- comment the code blocks of parameter settings for MovieLens-20M;
- uncomment the code blocks of parameter settings for Last.FM;
- ```
$ python main.py
```
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matched fp:5745d063af9fa6c4, topic:knowledge-graph, desc:knowledge graph