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

Automatic Data Visualization Generation from Chinese Natural Language Questions