GHRM

This is the code for the WWW 2021 Paper: Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval.

Usage

Data

Here are two datasets we used in our paper. After downloaded the whole datasets, you can put the queries.tsv and documents.tsv into the corresponding robust04 or clueweb09 subfolder in Data:

• Robust04: https://trec.nist.gov/data/cd45/index.html
• ClueWeb09-B: https://lemurproject.org/clueweb09/

Quick Start

You first need to process the data, for example: cd Data; and orderly running python preprocess.py , python bulid_dict.py, python gen_word_embeddings.py, python graph_construction.py and idf_construction.py.

Then you can run the file Code/run.py to train the model.

For example: cd Code; python run.py --model GHRM --gpuid 0 --qrl_len 4 --dataset robust04

Requirements

• Python 3.6+
• PyTorch 1.5.1

Citation

Please cite our paper if you use the code:

@inproceedings{yu2021graph,
title={Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval},
author={Yu, Xueli and Xu, Weizhi and Cui, Zeyu and Wu, Shu and Wang, Liang},
booktitle={Proceedings of the Web Conference 2021},
pages={778--787},
year={2021}
}