Controllable Gradient Item Retrieval

This repository is the PyTorch implementation of Controllable Gradient Item Retrieval (WWW 21).

arXiv

If you make use of the code/experiment, please cite our paper (Bibtex below).

@inproceedings{wang2021controllable,
  title={Controllable Gradient Item Retrieval},
  author={Wang, Haonan and Zhou, Chang and Yang, Carl and Yang, Hongxia and He, Jingrui},
  booktitle={Proceedings of the Web Conference 2021},
  pages={768--777},
  year={2021}
}

Contact: Haonan Wang (haonan3@illinois.edu)

Installation

Install PyTorch following the instuctions on the [official website] (https://pytorch.org/). The code has been tested over PyTorch 1.1.0 versions.

Then install the other dependencies.

conda env create -f environment.yml

Test run

Please download ml-20m and ml-25m from movielens, and then put them to data/ml-20m/raw/ and data/ml-25m/raw/ respectively.

Hyper-parameters need to be specified through the commandline arguments.

For item retrieval experiment, please refer run.sh.