Here we show how to generate the KG atomic files (*.kg and *.link) for Amazon-book dataset.
1.Clone the repository and install requirements. (If you have already done this, please move to the step 2.)
git clone https://github.com/RUCAIBox/RecDatasets
cd RecDatasets/conversion_tools
pip install -r requirements.txt
2.Download the KG file from Baidu Yun or Google Drive.
The used KG file is in KGDatasets/, named Amazon-book-KG.zip
unzip Amazon-book-KG.zip -d Amazon-book-KG
3.Get the inter atomic file.
You can refer to Amazon to get the inter atomic file of Amazon-book dataset, named Amazon_Books.inter
4.Go the conversion_tools/ directory
and run the following command to get the KG atomic files of Amazon-book dataset.
python add_knowledge.py --dataset Amazon_Books --inter_file Amazon_Books.inter \
--kg_data_path Amazon-book-KG --output_path training_data/Amazon_Books/ --hop 1
After this, we will get 'Amazon_Books.kg' and 'Amazon_Books.link' in training_data/Amazon_Books/.
dataset is the dataset name, we will use this parameter to name the *.kg and *.link file
inter_file is the input inter file
kg_data_path is the path of Amazon-book-KG obtained from Step 2
output_path is the path to store the converted kg atomic files
hop is the number of neighbor hops we generate for the items in knowledge graph. In our setting, the maximum is 3, default is 1.
Notes: You can change the relation by modifying Amazon-book-KG/relation.kg. This can remove those useless relations and reduce the scale of the generated knowledge graph.