dc.contributor.author | Lee, Ming-Chang | |
dc.contributor.author | Lin, Jia-Chun | |
dc.contributor.author | Stolz, Volker | |
dc.date.accessioned | 2024-07-10T08:52:13Z | |
dc.date.available | 2024-07-10T08:52:13Z | |
dc.date.created | 2024-06-07T10:04:00Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | International Conference on Pattern Recognition Applications and Methods (ICPRAM). 2024, 469-477. | en_US |
dc.identifier.uri | https://hdl.handle.net/11250/3139646 | |
dc.description.abstract | Despite the widespread use of k-means time series clustering in various domains, there exists a gap in the literature regarding its comprehensive evaluation with different time series preprocessing approaches. This paper seeks to fill this gap by conducting a thorough performance evaluation of k-means time series clustering on real-world open-source time series datasets. The evaluation focuses on two distinct techniques: z-normalization and NP-Free. The former is one of the most commonly used approaches for normalizing time series, and the latter is a real-time time series representation approach. The primary objective of this paper is to assess the impact of these two techniques on k-means time series clustering in terms of its clustering quality. The experiments employ the silhouette score, a well-established metric for evaluating the quality of clusters in a dataset. By systematically investigating the performance of k-means time series clustering with these two preprocessing tech niques, this paper addresses the current gap in k-means time series clustering evaluation and contributes valuable insights to the development of time series clustering | |
dc.description.abstract | Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free | |
dc.language.iso | eng | en_US |
dc.publisher | SciTePress | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free | en_US |
dc.title.alternative | Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | |
dc.source.pagenumber | 469-477 | en_US |
dc.source.journal | International Conference on Pattern Recognition Applications and Methods (ICPRAM) | en_US |
dc.identifier.doi | 10.5220/0012547200003654 | |
dc.identifier.cristin | 2274329 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |