| Autor: |
Jiazhe Wang, Xi Li, Chenlu Li, Di Peng, Arran Zeyu Wang, Yuhui Gu, Xingui Lai, Haifeng Zhang, Xinyue Xu, Xiaoqing Dong, Zhifeng Lin, Jiehui Zhou, Xingyu Liu, Wei Chen |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Visual Informatics, Vol 8, Iss 2, Pp 106-114 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2468-502X |
| DOI: |
10.1016/j.visinf.2024.06.002 |
| Popis: |
With the incredible growth of the scale and complexity of datasets, creating proper visualizations for users becomes more and more challenging in large datasets. Though several visualization recommendation systems have been proposed, so far, the lack of practical engineering inputs is still a major concern regarding the usage of visualization recommendations in the industry. In this paper, we proposed AVA, an open-sourced web-based framework for Automated Visual Analytics. AVA contains both empiric-driven and insight-driven visualization recommendation methods to meet the demands of creating aesthetic visualizations and understanding expressible insights respectively. The code is available at https://github.com/antvis/AVA. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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