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Data Horizons: An Analysis of AI Application Trends in Data Visualization

Published: 24 October 2024 Publication History

Abstract

The application of Artificial Intelligence (AI) in data visualization is revolutionizing the field by enhancing efficiency and accuracy. Advances in AI for data pattern recognition, analyzed through tools like the Web of Science toolkit and CiteSpace software, have accelerated data processing speeds and improved data representation precision. This allows users to gain deeper insights into data with unprecedented intuition. The integration of AI with business intelligence marks a new era of data visualization characterized by deep integration. The incorporation of technologies such as 6G, AIGC, AR/VR, and blockchain is expected to drive significant innovations in areas like intelligent assisted exploration, personalized services, deep integration, cross-border integration, ethics, and interpretability. This progression will lead data visualization towards a more intelligent, personalized, and interactive future, contributing to social progress, knowledge discovery, and enriching user experiences.

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Lu Yuyu, Qin Xue Di, Xie Yupeng, et al. "A Survey on Intelligent Data Visual Analysis Techniques." Journal of Software, 2024, 35(01): 356-404.
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Shi Guoji. "Research on the Application and Development of Data Visualization Technology in the Field of Big Data Analysis." Wireless Internet Technology, 2021, 18(18): 96-97.
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Mohaiminul Islam and Shang Jin. "An Overview of Data Visualization." 2019 International Conference on Information Science and Communications Technologies (ICISCT). 2019. 1-7.
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Zhang Yao, Wei Dong. "Re-examination of Data Visualization from Data Attributes and Design Logic." Packaging Engineering, 2022, 43(12): 234-240.
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  1. Data Horizons: An Analysis of AI Application Trends in Data Visualization

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    CAIBDA '24: Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms
    June 2024
    1206 pages
    ISBN:9798400710247
    DOI:10.1145/3690407
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 24 October 2024

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    Author Tags

    1. Artificial Intelligence (AI)
    2. Data Visualization
    3. Deep Learning
    4. Machine Learning

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