This repository is the implementation of MKR (arXiv):

Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
Hongwei Wang, Fuzheng Zhang, Miao Zhao, Wenjie Li, Xing Xie, and Minyi Guo.
In Proceedings of The 2019 Web Conference (WWW 2019)

MKR is a Multi-task learning approach for Knowledge graph enhanced Recommendation. MKR consists of two parts: the recommender system (RS) module and the knowledge graph embedding (KGE) module. The two modules are bridged by cross&compress units, which can automatically learn high-order interactions of item and entity features and transfer knowledge between the two tasks.

• data/
  • book/
    • BX-Book-Ratings.csv: raw rating file of Book-Crossing dataset;
    • 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;
  • 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;
    • ratrings.dat: raw rating file of MovieLens-1M;
  • 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;
  • intersect-14m/
    • ratings_re2.csv : rating file of MovieLens-14M;
    • triples_idx2.txt : KG obtained from DBpedia
• src/: implementations of MKR.
• log/ : log of every training and model saved from every epoch
• test/ : evaluation of the model

You can download the intersect-20m dataset here. Copy all items inside and put into /movie folder except the Preprocess.ipynb.

pip3 install -r requirements.txt

1. To create missing kg_final.txt & ratings_final.txt files:

• use this jupyter notebook (Preprocess.ipynb inside the ./data/intersect-14m).

1. Make sure kg_final.txt & ratings_final.txt exist. If not, run the preprocessing first.
2. Train the data (this command will train the data using default hyperparameter)

   python3 src/main.py --dataset intersect-14m
   

To start using new dataset, or if dataset changed, those file need to be deleted, and re preprocess it, otherwise it will use old dataset:

• data/movie/ratings_final.npy
• data/movie/kg_final.npy

There are several ways to do this :

1. Open src/main.py and change the args parser default value
2. run src/main.py with arguments required.