Published in JIDM, 2021
Jacintho, L. H. M., da Silva, T. P., Parmezan, A. R. S., & Batista, G. E. A. P. A. (2021). Analyzing Spatio-Temporal Voting Patterns in Brazilian Elections Through a Simple Data Science Pipeline
Published in KDMILE, 2020
Jacintho, L. H. M., da Silva, T. P., Parmezan, A. R. S., & Batista, G. E. A. P. A. (2020, October). Brazilian Presidential Elections: Analysing Voting Patterns in Time and Space Using a Simple Data Science Pipeline. In Anais do VIII Symposium on Knowledge Discovery, Mining and Learning (pp. 217-224). SBC.
Published in BRACIS, 2020
Cristiani, A. L., da Silva, T. P., & de Arruda Camargo, H. (2020, October). A Fuzzy Approach for Classification and Novelty Detection in Data Streams Under Intermediate Latency. In Brazilian Conference on Intelligent Systems (pp. 171-186). Springer, Cham.
Published in FUZZ-IEEE, 2020
T. P. da Silva and H. de Arruda Camargo, “Possibilistic Approach For Novelty Detection In Data Streams,” 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2020, pp. 1-8, doi: 10.1109/FUZZ48607.2020.9177582.
Published in CIARP, 2018
da Silva, T. P., Souza, V. M. A., Batista, G. E. A. P. A., & de Arruda Camargo, H. (2018, November). A fuzzy classifier for data streams with infinitely delayed labels. In Iberoamerican Congress on Pattern Recognition (pp. 287-295). Springer, Cham.
Published in BRACIS, 2018
V. Souza, T. Pinho and G. Batista, “Evaluating Stream Classifiers with Delayed Labels Information,” 2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 2018, pp. 408-413, doi: 10.1109/BRACIS.2018.00077.
Published in FUZZ-IEEE, 2018
T. P. da Silva, L. Schick, P. de Abreu Lopes and H. de Arruda Camargo, “A Fuzzy Multiclass Novelty Detector for Data Streams,” 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2018, pp. 1-8, doi: 10.1109/FUZZ-IEEE.2018.8491545.
Published in BRACIS, 2017
T. P. da Silva, G. A. Urban, P. De Abreu Lopes and H. de Arruda Camargo, “A Fuzzy Variant for On-Demand Data Stream Classification,” 2017 Brazilian Conference on Intelligent Systems (BRACIS), 2017, pp. 67-72, doi: 10.1109/BRACIS.2017.60.