Research Article
Performance Evaluation: Ball-Treeand KD-Tree in the Context of MST
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@INPROCEEDINGS{10.1007/978-3-642-32573-1_38, author={Hazarath Munaga and Venkata Jarugumalli}, title={Performance Evaluation: Ball-Treeand KD-Tree in the Context of MST}, proceedings={Signal Processing and Information Technology. First International Joint Conference, SPIT 2011 and IPC 2011, Amsterdam, The Netherlands, December 1-2, 2011, Revised Selected Papers}, proceedings_a={SPIT \& IPC}, year={2012}, month={10}, keywords={Euclidean Minimum Spanning Tree (EMST) dual Tree kd-tree ball-tree}, doi={10.1007/978-3-642-32573-1_38} }- Hazarath Munaga
Venkata Jarugumalli
Year: 2012
Performance Evaluation: Ball-Treeand KD-Tree in the Context of MST
SPIT & IPC
Springer
DOI: 10.1007/978-3-642-32573-1_38
Abstract
Now a day’s many algorithms are invented / being inventing to find the solution for Euclidean Minimum Spanning Tree () problem, as its applicability is increasing in much wide range of fields containing spatial / spatio – temporal data viz. astronomy which consists of millions of spatial data. To solve this problem, we are presenting a technique by adopting the dual tree algorithm for finding efficient EMST and experimented on a variety of real time and synthetic datasets. This paper presents the observed experimental observations and the efficiency of the dual tree framework,in the context of kd-tree and ball-tree on spatial datasets of different dimensions.
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