| Full text | |
| Author(s): |
Vega-Oliveros, Didier A.
;
Cotacallapa, Moshe
;
Ferreira, Leonardo N.
;
Quiles, Marcos G.
;
Zhao, Liang
;
Macau, Elbert E. N.
;
Cardoso, Manoel F.
;
Assoc Comp Machinery
Total Authors: 8
|
| Document type: | Journal article |
| Source: | SAC '19: PROCEEDINGS OF THE 34TH ACM/SIGAPP SYMPOSIUM ON APPLIED COMPUTING; v. N/A, p. 8-pg., 2019-01-01. |
| Abstract | |
Network theory has established itself as an appropriate tool for complex systems analysis and pattern recognition. In the context of spatiotemporal data analysis, correlation networks are used in the vast majority of works. However, the Pearson correlation coefficient captures only linear relationships and does not correctly capture recurrent events. This missed information is essential for temporal pattern recognition. In this work, we propose a chronological network construction process that is capable of capturing various events. Similar to the previous methods, we divide the area of study into grid cells and represent them by nodes. In our approach, links are established if two consecutive events occur in two different nodes. Our method is computationally efficient, adaptable to different time windows and can be applied to any spatiotemporal data set. As a proof-of-concept, we evaluated the proposed approach by constructing chronological networks from the MODIS dataset for fire events in the Amazon basin. We explore two data analytic approaches: one static and another temporal. The results show some activity patterns on the fire events and a displacement phenomenon over the year. The validity of the analyses in this application indicates that our data modeling approach is very promising for spatio-temporal data mining. (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: | 18/01722-3 - Semi-supervised learning via complex networks: network construction, selection and propagation of labels and applications |
| Grantee: | Lilian Berton |
| Support Opportunities: | Regular Research Grants |
| 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 |
| 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: | 11/18496-7 - Dynamic semi-supervised and active learning based on complex networks |
| Grantee: | Marcos Gonçalves Quiles |
| Support Opportunities: | Research Grants - Young Investigators Grants |
| FAPESP's process: | 17/05831-9 - Analysis of climate indexes influence on wildfires using complex networks and data mining |
| Grantee: | Leonardo Nascimento Ferreira |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 16/16291-2 - Characterizing time-varying networks: methods and applications |
| Grantee: | Marcos Gonçalves Quiles |
| Support Opportunities: | Scholarships abroad - Research |