Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Minji | - |
dc.contributor.author | Oh, Hee-Seok | - |
dc.contributor.author | Lim, Yaeji | - |
dc.date.accessioned | 2023-07-27T05:44:02Z | - |
dc.date.available | 2023-07-27T05:44:02Z | - |
dc.date.issued | 2023-07 | - |
dc.identifier.issn | 0176-4268 | - |
dc.identifier.issn | 1432-1343 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/67292 | - |
dc.description.abstract | This study develops a new clustering method for high-dimensional zero-inflated time series data. The proposed method is based on thick-pen transform (TPT), in which the basic idea is to draw along the data with a pen of a given thickness. Since TPT is a multi-scale visualization technique, it provides some information on the temporal tendency of neighborhood values. We introduce a modified TPT, termed 'ensemble TPT (e-TPT)', to enhance the temporal resolution of zero-inflated time series data that is crucial for clustering them efficiently. Furthermore, this study defines a modified similarity measure for zero-inflated time series data considering e-TPT and proposes an efficient iterative clustering algorithm suitable for the proposed measure. Finally, the effectiveness of the proposed method is demonstrated by simulation experiments and two real datasets: step count data and newly confirmed COVID-19 case data. | - |
dc.format.extent | 25 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | SPRINGER | - |
dc.title | Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/s00357-023-09437-z | - |
dc.identifier.bibliographicCitation | JOURNAL OF CLASSIFICATION, v.40, no.2, pp 407 - 431 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.wosid | 001004800800001 | - |
dc.identifier.scopusid | 2-s2.0-85161679897 | - |
dc.citation.endPage | 431 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 407 | - |
dc.citation.title | JOURNAL OF CLASSIFICATION | - |
dc.citation.volume | 40 | - |
dc.type.docType | Article | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | Clustering | - |
dc.subject.keywordAuthor | Multiscale method | - |
dc.subject.keywordAuthor | Newly confirmed COVID-19 case data | - |
dc.subject.keywordAuthor | Step count data | - |
dc.subject.keywordAuthor | Thick-pen transform | - |
dc.subject.keywordAuthor | Zero-inflated time series data | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalResearchArea | Psychology | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Psychology, Mathematical | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
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