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Visual Clustering Factors in Scatterplots.
- Source :
- IEEE Computer Graphics & Applications; Sep/Oct2021, Vol. 41 Issue 5, p79-89, 11p
- Publication Year :
- 2021
-
Abstract
- Cluster analysis is an important technique in data analysis. However, there is no encompassing theory on scatterplots to evaluate clustering. Human visual perception is regarded as a gold standard to evaluate clustering. The cluster analysis based on human visual perception requires the participation of many probands, to obtain diverse data, and hence is a challenge to do. We contribute an empirical and data-driven study on human perception for visual clustering of large scatterplot data. First, we systematically construct and label a large, publicly available scatterplot dataset. Second, we carry out a qualitative analysis based on the dataset and summarize the influence of visual factors on clustering perception. Third, we use the labeled datasets to train a deep neural network for modeling human visual clustering perception. Our experiments show that the data-driven model successfully models the human visual perception, and outperforms conventional clustering algorithms in synthetic and real datasets. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02721716
- Volume :
- 41
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- IEEE Computer Graphics & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 153648992
- Full Text :
- https://doi.org/10.1109/MCG.2021.3098804