The Effectiveness of Graph Contrastive Learning on Mathematical Information Retrieval

Pei-Syuan Wang; Hung-Hsuan Chen

The Effectiveness of Graph Contrastive Learning on Mathematical Information Retrieval

Information Retrieval 2024-02-22 v1

Authors: Pei-Syuan Wang , Hung-Hsuan Chen

Abstract

This paper details an empirical investigation into using Graph Contrastive Learning (GCL) to generate mathematical equation representations, a critical aspect of Mathematical Information Retrieval (MIR). Our findings reveal that this simple approach consistently exceeds the performance of the current leading formula retrieval model, TangentCFT. To support ongoing research and development in this field, we have made our source code accessible to the public at https://github.com/WangPeiSyuan/GCL-Formula-Retrieval/.

Keywords

mathematical information retrieval graph contrastive learning formula retrieval equation representation empirical study

Cite

@article{arxiv.2402.13444,
  title  = {The Effectiveness of Graph Contrastive Learning on Mathematical Information Retrieval},
  author = {Pei-Syuan Wang and Hung-Hsuan Chen},
  journal= {arXiv preprint arXiv:2402.13444},
  year   = {2024}
}

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