Automatic Data Visualization Generation from Chinese Natural Language Questions

Yan Ge, Victor Junqiu Wei, Yuanfeng Song, Jason Chen Zhang, Raymond Chi-Wing Wong
9/14/2023
cs.CL

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Abstract

Data visualization has emerged as an effective tool for getting insights from massive datasets. Due to the hardness of manipulating the programming languages of data visualization, automatic data visualization generation from natural languages (Text-to-Vis) is becoming increasingly popular. Despite the plethora of research effort on the English Text-to-Vis, studies have yet to be conducted on data visualization generation from questions in Chinese. Motivated by this, we propose a Chinese Text-to-Vis dataset in the paper and demonstrate our first attempt to tackle this problem. Our model integrates multilingual BERT as the encoder, boosts the cross-lingual ability, and infuses the $n$-gram information into our word representation learning. Our experimental results show that our dataset is challenging and deserves further research.

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Cite this paper

@article{ge2023automatic,
  title  = {Automatic Data Visualization Generation from Chinese Natural Language Questions},
  author = {Yan Ge and Victor Junqiu Wei and Yuanfeng Song and Jason Chen Zhang and Raymond Chi-Wing Wong},
  year   = {2023},
  eprint = {2309.07650},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.07650v1}
}

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