Extracting the Boundaries of Clusters: A Post-Clustering Tool for Spatial Datasets

Date

2020-04-01

Author

İNKAYA, TÜLİN
Kayaligil, Sinan
Özdemirel, Nur Evin

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Boundary extraction is a fundamental post-clustering problem. It facilitates interpretability and usability of clustering results. Also, it provides visualization and dataset reduction. However, it has not attracted much attention compared to the clustering problem itself. In this work, we address the boundary extraction of clusters in 2- and 3-dimensional spatial datasets. We propose two algorithms based on Delaunay Triangulation (DT). Numerical experiments show that the proposed algorithms generate the cluster boundaries effectively. Also, they yield significant amounts of dataset reduction.

Subject Keywords

Software, Artificial Intelligence, Computer Vision and Pattern Recognition

URI

https://hdl.handle.net/11511/35246

Journal

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE

DOI

https://doi.org/10.1142/s0218001420500081

Collections

Department of Industrial Engineering, Article

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Citation Formats

T. İNKAYA, S. Kayaligil, and N. E. Özdemirel, “Extracting the Boundaries of Clusters: A Post-Clustering Tool for Spatial Datasets,” INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35246.