https://scholars.lib.ntu.edu.tw/handle/123456789/638457
Title: | Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator | Authors: | Yu, Jen Chien Yang, Chun Chieh Gilbert, John Reuben Liu, Rou Jun Oyang, Yen-Jen Yang, Meng Han |
Keywords: | Clustering analysis | Kernel density estimation | Spatiotemporal data | Issue Date: | 1-Jan-2023 | Source: | Proceedings - International Conference on Machine Learning and Cybernetics | Abstract: | A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/638457 | ISBN: | 9798350303780 | ISSN: | 2160133X | DOI: | 10.1109/ICMLC58545.2023.10327996 |
Appears in Collections: | 生醫電子與資訊學研究所 |
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