qingkaizeng/taxorec

TaxoRec

This repository contains a implementation of our "Enhancing Recommendation with Automated TagTaxonomy Construction in Hyperbolic Space" accepted by ICDE 2022.

Environment Setup

1. Pytorch 1.8.1
2. Python 3.7.3

Guideline

data

We provide one dataset, ciao.

adj_csr.npz adj matrix built for training gcn item_tag_matrix.npz items attributes matrix tag_map.json tag idx to tag name mapping. train.pkl train set test.pkl test set user_item_list.pkl user-item dict for the complete dataset.

models

The implementation of model(model.py);

code to implement Hyperbolic gcn (encoders.py, hyp_layers.py)

utils

data_generator.py read and organize data helper.py some method for helping preprocess data or set seeds and devices sampler.py a parallel sampler to sample batches for training taxogen.py build taxonomy train_utils.py read and parse the config arguments

Example to run the codes

python run.py

Citation

If you find the code useful, please consider citing the following paper:

@inproceedings{tan2022enhancing,
  title={Enhancing Recommendation with Automated TagTaxonomy Construction in Hyperbolic Space},
  author={Tan, Yanchao and Yang, Carl and Wei, Xiangyu and Chen, Chaochao and Li, Longfei and Zheng, Xiaolin},
  booktitle={2022 IEEE 38th International Conference on Data Engineering (ICDE)},
  year={2022},
  organization={IEEE}
}