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Extracting the boundaries of clusters: A post-clustering tool for spatial datasets

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İnkaya, Tulin

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Kayalıgil, Sinan
Özdemirel, Nur Evin

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World Scientific Publ Co Pte Ltd

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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.

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Defect patterns, Shape, Set, Algorithm, Points, Region, Segmentation, Computation, Border, Boundary extraction, Clustering, Data mining, Dataset reduction, Data visualization, Science & technology, Technology, Computer science, artificial intelligence

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