| Full text | |
| Author(s): |
Rodrigues, Caroline Mazini
[1]
;
Soriano-Vargas, Aurea
[1]
;
Lavi, Bahram
[1]
;
Rocha, Anderson
[1]
;
Dias, Zanoni
[1]
Total Authors: 5
|
| Affiliation: | [1] Univ Estadual Campinas, Inst Comp, BR-13083852 Campinas - Brazil
Total Affiliations: 1
|
| Document type: | Journal article |
| Source: | IEEE Transactions on Information Forensics and Security; v. 16, p. 2957-2972, 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
Information coming from social media is vital to the understanding of the dynamics involved in multiple events such as terrorist attacks and natural disasters. With the spread and popularization of cameras and the means to share content through social networks, an event can be followed through many different lenses and vantage points. However, social media data present numerous challenges, and frequently it is necessary a great deal of data cleaning and filtering techniques to separate what is related to the depicted event from contents otherwise useless. In a previous effort of ours, we decomposed events into representative components aiming at describing vital details of an event to characterize its defining moments. However, the lack of minimal supervision to guide the combination of representative components somehow limited the performance of the method. In this paper, we extend upon our prior work and present a learning-from-data method for dynamically learning the contribution of different components for a more effective event representation. The method relies upon just a few training samples (few-shot learning), which can be easily provided by an investigator. The obtained results on real-world datasets show the effectiveness of the proposed ideas. (AU) | |
| FAPESP's process: | 18/16548-9 - Learning Visual Clues of the Passage of Time |
| Grantee: | Luis Augusto Martins Pereira |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 18/16214-3 - Heterogeneous data analysis for event detection |
| Grantee: | Caroline Mazini Rodrigues |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 17/16246-0 - Sensitive media analysis through deep learning architectures |
| Grantee: | Sandra Eliza Fontes de Avila |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 15/11937-9 - Investigation of hard problems from the algorithmic and structural stand points |
| Grantee: | Flávio Keidi Miyazawa |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 18/05668-3 - Feature-space-time Coherence with Heterogeneous Data |
| Grantee: | Bahram Lavi Sefidgari |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 13/08293-7 - CCES - Center for Computational Engineering and Sciences |
| Grantee: | Munir Salomao Skaf |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 17/16871-1 - Problems of sorting permutations by fragmentation-weighted operations |
| Grantee: | Alexsandro Oliveira Alexandrino |
| Support Opportunities: | Scholarships in Brazil - Master |