面向数据可视化的自然语言接口研究综述OA北大核心CSTPCD

The long-standing goal in the field of data visualization has been to find a solution that directly generates visu-alizations from natural language.Research on natural language interfaces(NLI)provides a new approach to this field.This interface accepts queries in the form of natural language and tabular datasets as input and outputs corresponding visu-alization renderings.Simultaneously,as an auxiliary input method,traditional users need to convert analytical intents into a series of logical operations and interact with them,such as programming instructions or graphical interface operations.Combining the use of natural language interfaces for data visualization(DV-NLI)enables users to focus on visualization tasks without worrying about how to operate visualization tools.In recent years,with the rise of large language models(LLM)such as GPT-3 and GPT-4,research on integrating LLM with visualization has become a hot topic.This paper pro-vides a comprehensive review of existing DV-NLIs and supplements them with the latest research.Based on their imple-mentation methods,DV-NLIs are categorized into symbolic NLP methods,deep learning model methods,and large lan-guage model methods.It also analyzes and discusses relevant techniques under each category.Finally,the paper summa-rizes and looks forward to future work in DV-NLI.