A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization
Without a form of visual feedback, multivariate data would be reduced to a lump of numbers that very few people would be able to appreciate and be benefited from. This research paper proposes a novel triangulate mapping technique based on selforganizing anchor points for multivariate data visualizat...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Published: |
American Scientific Publishers
2017
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/18827/ |
| _version_ | 1848838587898920960 |
|---|---|
| author | Yii, Ming Leong Teh, Chee Siong |
| author_facet | Yii, Ming Leong Teh, Chee Siong |
| author_sort | Yii, Ming Leong |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Without a form of visual feedback, multivariate data would be reduced to a lump of numbers that very few people would be able to appreciate and be benefited from. This research paper proposes a novel triangulate mapping technique based on selforganizing anchor points for multivariate data visualization. Self-Organizing Map (SOM) and a modified Adaptive Coordinates (AC) are hybridized to produce the anchor points in the 2D space. The trained anchor points are used to triangulate data onto a topologically preserved 2D space. The empirical studies that produce topologically preserved data visualizations for high dimension and arbitrarily shaped clusters in simulated, benchmarking, and real-life dataset show its usefulness in providing intuitive visual feedback to the user. |
| first_indexed | 2025-11-15T06:57:56Z |
| format | Article |
| id | unimas-18827 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| last_indexed | 2025-11-15T06:57:56Z |
| publishDate | 2017 |
| publisher | American Scientific Publishers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-188272017-12-12T02:05:19Z http://ir.unimas.my/id/eprint/18827/ A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization Yii, Ming Leong Teh, Chee Siong QA Mathematics QA75 Electronic computers. Computer science Without a form of visual feedback, multivariate data would be reduced to a lump of numbers that very few people would be able to appreciate and be benefited from. This research paper proposes a novel triangulate mapping technique based on selforganizing anchor points for multivariate data visualization. Self-Organizing Map (SOM) and a modified Adaptive Coordinates (AC) are hybridized to produce the anchor points in the 2D space. The trained anchor points are used to triangulate data onto a topologically preserved 2D space. The empirical studies that produce topologically preserved data visualizations for high dimension and arbitrarily shaped clusters in simulated, benchmarking, and real-life dataset show its usefulness in providing intuitive visual feedback to the user. American Scientific Publishers 2017 Article PeerReviewed Yii, Ming Leong and Teh, Chee Siong (2017) A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization. Advance Science Letters, 23 (11). pp. 11083-11087. ISSN 1936-6612 http://www.aspbs.com/science.htm |
| spellingShingle | QA Mathematics QA75 Electronic computers. Computer science Yii, Ming Leong Teh, Chee Siong A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization |
| title | A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization |
| title_full | A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization |
| title_fullStr | A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization |
| title_full_unstemmed | A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization |
| title_short | A Novel Triangulate Mapping Based on Self- Organized Anchor Points for Data Visualization |
| title_sort | novel triangulate mapping based on self- organized anchor points for data visualization |
| topic | QA Mathematics QA75 Electronic computers. Computer science |
| url | http://ir.unimas.my/id/eprint/18827/ http://ir.unimas.my/id/eprint/18827/ |