Implementation of Minimum Edge Constraints Sets for Proximity Graphs
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For certain edge-constrained proximity algorithms, not every edge of the resulting graph needs to be explicitly stored. This has implications for graph compression. We examine the application and runtime performance on minimum edge-constrained algorithms for three proximity graph types: Delaunay triangulation, Gabriel graph and minimum spanning tree.Implementation details on these algorithms are given, their performance in both large real world datasets and randomized datasets are evaluated. In addition, their compression metrics, the number of edges that are reduced from the constraint edge set, are investigated.
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Copyright © 2018 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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duong-implementationofminimumedgeconstraintssets.pdf | 2023-05-05 | Public | Download |