https://scholars.lib.ntu.edu.tw/handle/123456789/497185
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Chin, Wei-Chien-Benny | en_US |
dc.contributor.author | Wen, Tzai-Hung | en_US |
dc.contributor.author | Sabel, Clive E. | en_US |
dc.contributor.author | I-HSIANG WANG | en_US |
dc.contributor.author | Wen T.-H. | en_US |
dc.creator | Chin, Wei-Chien-Benny;Wen, Tzai-Hung;Sabel, Clive E.;Wang, I.-Hsiang | - |
dc.date.accessioned | 2020-06-04T07:49:45Z | - |
dc.date.available | 2020-06-04T07:49:45Z | - |
dc.date.issued | 2017 | - |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | https://scholars.lib.ntu.edu.tw/handle/123456789/497185 | - |
dc.description.abstract | A diffusion process can be considered as the movement of linked events through space and time. Therefore, space-time locations of events are key to identify any diffusion process. However, previous clustering analysis methods have focused only on space-time proximity characteristics, neglecting the temporal lag of the movement of events. We argue that the temporal lag between events is a key to understand the process of diffusion movement. Using the temporal lag could help to clarify the types of close relationships. This study aims to develop a data exploration algorithm, namely the TrAcking Progression In Time And Space (TaPiTaS) algorithm, for understanding diffusion processes. Based on the spatial distance and temporal interval between cases, TaPiTaS detects sub-clusters, a group of events that have high probability of having common sources, identifies progression links, the relationships between sub-clusters, and tracks progression chains, the connected components of sub-clusters. Dengue Fever cases data was used as an illustrative case study. The location and temporal range of sub-clusters are presented, along with the progression links. TaPiTaS algorithm contributes a more detailed and in-depth understanding of the development of progression chains, namely the geographic diffusion process. ? 2017 The Author(s). | - |
dc.relation.ispartof | Scientific Reports | - |
dc.subject.classification | [SDGs]SDG3 | - |
dc.title | A geo-computational algorithm for exploring the structure of diffusion progression in time and space | en_US |
dc.type | journal article | en |
dc.identifier.doi | 10.1038/s41598-017-12852-z | - |
dc.identifier.isi | WOS:000412138800001 | - |
dc.relation.pages | 12565 | - |
dc.relation.journalvolume | 7 | - |
item.cerifentitytype | Publications | - |
item.openairetype | journal article | - |
item.fulltext | no fulltext | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
crisitem.author.dept | Electrical Engineering | - |
crisitem.author.dept | MediaTek-NTU Research Center | - |
crisitem.author.dept | Geography | - |
crisitem.author.orcid | 0000-0002-9151-8336 | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
crisitem.author.parentorg | College of Science | - |
顯示於: | 電機工程學系 |
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