Visual exploration of multi-dimensional data via rule-based sample embedding
We propose an approach to learning sample embedding for analyzing multi-dimensional datasets. The basic idea is to extract rules from the given dataset and learn the embedding for each sample based on the rules it satisfies. The approach can filter out pattern-irrelevant attributes, leading to signi...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-09-01
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| Series: | Visual Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468502X24000469 |
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| author | Tong Zhang Jie Li Chao Xu |
| author_facet | Tong Zhang Jie Li Chao Xu |
| author_sort | Tong Zhang |
| collection | DOAJ |
| description | We propose an approach to learning sample embedding for analyzing multi-dimensional datasets. The basic idea is to extract rules from the given dataset and learn the embedding for each sample based on the rules it satisfies. The approach can filter out pattern-irrelevant attributes, leading to significant visual structures of samples satisfying the same rules in the projection. In addition, analysts can understand a visual structure based on the rules that the involved samples satisfy, which improves the projection’s pattern interpretability. Our research involves two methods for achieving and applying the approach. First, we give a method to learn rule-based embedding for each sample. Second, we integrate the method into a system to achieve an analytical workflow. Cases on real-world dataset and quantitative experiment results show the usability and effectiveness of our approach. |
| format | Article |
| id | doaj-art-fd44b85d9e4040fc8019d158dab0bc1b |
| institution | OA Journals |
| issn | 2468-502X |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Visual Informatics |
| spelling | doaj-art-fd44b85d9e4040fc8019d158dab0bc1b2025-08-20T02:12:28ZengElsevierVisual Informatics2468-502X2024-09-0183535610.1016/j.visinf.2024.09.005Visual exploration of multi-dimensional data via rule-based sample embeddingTong Zhang0Jie Li1Chao Xu2College of Intelligence and Computing, Tianjin University, Tianjin, ChinaCorresponding author.; College of Intelligence and Computing, Tianjin University, Tianjin, ChinaCollege of Intelligence and Computing, Tianjin University, Tianjin, ChinaWe propose an approach to learning sample embedding for analyzing multi-dimensional datasets. The basic idea is to extract rules from the given dataset and learn the embedding for each sample based on the rules it satisfies. The approach can filter out pattern-irrelevant attributes, leading to significant visual structures of samples satisfying the same rules in the projection. In addition, analysts can understand a visual structure based on the rules that the involved samples satisfy, which improves the projection’s pattern interpretability. Our research involves two methods for achieving and applying the approach. First, we give a method to learn rule-based embedding for each sample. Second, we integrate the method into a system to achieve an analytical workflow. Cases on real-world dataset and quantitative experiment results show the usability and effectiveness of our approach.http://www.sciencedirect.com/science/article/pii/S2468502X24000469Tabular dataMulti-dimensional explorationEmbedding projectionRuleVisual analytics |
| spellingShingle | Tong Zhang Jie Li Chao Xu Visual exploration of multi-dimensional data via rule-based sample embedding Visual Informatics Tabular data Multi-dimensional exploration Embedding projection Rule Visual analytics |
| title | Visual exploration of multi-dimensional data via rule-based sample embedding |
| title_full | Visual exploration of multi-dimensional data via rule-based sample embedding |
| title_fullStr | Visual exploration of multi-dimensional data via rule-based sample embedding |
| title_full_unstemmed | Visual exploration of multi-dimensional data via rule-based sample embedding |
| title_short | Visual exploration of multi-dimensional data via rule-based sample embedding |
| title_sort | visual exploration of multi dimensional data via rule based sample embedding |
| topic | Tabular data Multi-dimensional exploration Embedding projection Rule Visual analytics |
| url | http://www.sciencedirect.com/science/article/pii/S2468502X24000469 |
| work_keys_str_mv | AT tongzhang visualexplorationofmultidimensionaldataviarulebasedsampleembedding AT jieli visualexplorationofmultidimensionaldataviarulebasedsampleembedding AT chaoxu visualexplorationofmultidimensionaldataviarulebasedsampleembedding |