| Full text | |
| Author(s): |
Anghinoni, Leandro
[1]
;
Vega-Oliveros, Didier A.
[2, 3]
;
Silva, Thiago Christiano
[4, 5]
;
Zhao, Liang
[5]
Total Authors: 4
|
| Affiliation: | [1] Univ Sao Paulo, ICMC, Sao Carlos, SP - Brazil
[2] Univ Estadual Campinas, Inst Comp, Campinas, SP - Brazil
[3] Indiana Univ, Ctr Complex Networks & Syst Res, Luddy Sch Informat Comp & Engn, Bloomington, IN - USA
[4] Univ Catolica Brasilia, Brasilia, DF - Brazil
[5] Univ Sao Paulo, FFCLRP, Ribeirao Preto, SP - Brazil
Total Affiliations: 5
|
| Document type: | Journal article |
| Source: | European Physical Journal-Special Topics; v. 230, n. 14-15, p. 2775-2782, OCT 2021. |
| Web of Science Citations: | 1 |
| Abstract | |
Identifying time series patterns is of great importance for many real-world problems in a variety of scientific fields. Here, we present a method to identify time series patterns in multiscale levels based on the hierarchical community representation in a complex network. The construction method transforms the time series into a network according to its segments' correlation. The constructed network's quality is evaluated in terms of the largest correlation threshold that reaches the largest main component's size. The presence of repeated hierarchical patterns is then captured through network metrics, such as the modularity along the community detection process. We show the benefits of the proposed method by testing in one artificial dataset and two real-world time series applications. The results indicate that the method can successfully identify the original data's hierarchical (micro and macro) characteristics. (AU) | |
| FAPESP's process: | 18/24260-5 - Spatiotemporal Data Analytics based on Complex Networks |
| Grantee: | Didier Augusto Vega Oliveros |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 19/26283-5 - Learning visual clues of the passage of time |
| Grantee: | Didier Augusto Vega Oliveros |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 16/23698-1 - Dynamical Processes in Complex Network based on Machine Learning |
| Grantee: | Didier Augusto Vega Oliveros |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 15/50122-0 - Dynamic phenomena in complex networks: basics and applications |
| Grantee: | Elbert Einstein Nehrer Macau |
| Support Opportunities: | Research Projects - Thematic Grants |