International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 72 | Issue 8 | Year 2024 | Article Id. IJCTT-V72I8P115 | DOI : https://doi.org/10.14445/22312803/

Visualizing Higher-Dimensional Data

Atmajitsinh Gohil

Received Revised Accepted Published
18 Jun 2024 22 Jul 2024 11 Aug 2024 30 Aug 2024

Citation :

Atmajitsinh Gohil, "Visualizing Higher-Dimensional Data," International Journal of Computer Trends and Technology (IJCTT), vol. 72, no. 8, pp. 104-108, 2024. Crossref, https://doi.org/10.14445/22312803/

Abstract

The advances in technology have led to generating not only large volumes of data but also at a higher frequency. The data generated is dynamic and available in different formats. The data generated in the present time is thus higher dimensional data. The primary objective of the paper is to review the data visualization techniques for summarizing and interpreting higher dimensional data. The paper studies the challenges of higher dimensional data and addresses the same through various visualization techniques.

Keywords

Data visualization, High dimensional data, Artificial Intelligence, Data analysis techniques, Data visualization tools.

References

[1] D. Srivastava, “An Introduction to Data Visualization Tools and Techniques in Various Domains,” International Journal of Computer Trends Technology, vol. 71, no. 4, pp.125-30, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Nathan Yau, Data Points: Visualization that Means Something, John Wiley & Sons, 2013.
[Google Scholar] [Publisher Link]
[3] Evgeniy Yur’evich Gorodov, and Vasiliy Vasil’evich Gubarev, “Analytical Review of Data Visualization Methods in Application to Big Data,” Journal of Electrical and Computer Engineering, vol. 2013, no. 1, pp. 1-7, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Herman Chernoff, “The Use of Faces to Represent Points in K-Dimensional Space Graphically,” Journal of the American Statistical Association, vol. 68, no. 342 pp. 361-368, 1973.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Martijn Tennekes, and Edwin de Jonge, “Top-Down Data Analysis with Treemaps,” In Proceedings of the International Conference on Imaging Theory and Applications, Vilamoura, Algarve, Portugal, vol. 2, pp. 236-241, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Paul Embrechts, and Agnes M. Herzberg, Variations of Andrews’ Plots, International Statistical Review / Revue Internationale de Statistique, vol. 59, no. 2, pp. 175-194, 1991.
[CrossRef] [Google Scholar] [Publisher Link]