Towards Natural Language Interfaces for Data Visualization: A Survey

• Published in: arXiv.org
• Main Authors: Shen, Leixian, Shen, Enya, Luo, Yuyu, Yang, Xiaocong, Hu, Xuming, Zhang, Xiongshuai, Tai, Zhiwei, Wang, Jianmin
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 04.02.2022
• Subjects: Computer Science - Human-Computer Interaction; Natural language; Natural language processing; Scientific visualization; User experience; User interfaces; Visualization
• DOI: 10.48550/arxiv.2109.03506

Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary input modality to direct manipulation for visual analytics can provide an engaging user experience. It enables users to focus on their tasks rather than having to worry about how to operate visualization tools on the interface. In the past two decades, leveraging advanced natural language processing technologies, numerous V-NLI systems have been developed in academic research and commercial software, especially in recent years. In this article, we conduct a comprehensive review of the existing V-NLIs. In order to classify each paper, we develop categorical dimensions based on a classic information visualization pipeline with the extension of a V-NLI layer. The following seven stages are used: query interpretation, data transformation, visual mapping, view transformation, human interaction, dialogue management, and presentation. Finally, we also shed light on several promising directions for future work in the V-NLI community.