3rd Brazilian Competition on Knowledge Discovery in Databases (KDD-BR 2019)
The Brazilian competition on Knowledge Discovery in Databases (KDD-BR) was firstly launched in the 2017 joint editions of the Brazilian Conference on Intelligent Systems (BRACIS), the Brazilian Symposium on Databases (SBBD) and the Symposium on Knowledge Discovery, Mining and Learning (KDMiLe), at Uberlândia-MG, Brazil. This first edition involved classifying images captured by one of the monitoring stations of the EXOSS Citizen Science organization, which monitors meteors crossing the southern skies. The second edition was held in partnership with the IBM research center in São Paulo, as part of the BRACIS and KDMile events. The objective was to predict the production of palm oil harvests from the company AGROPALMA.
This year the third edition of the KDD-BR competition will be one of the activities of the BRACIS conference, which will take place in Salvador, Bahia, from October 15 to 18, 2019. The challenge will involve a real predictive problem of a company, to be revealed soon. The competition will be hosted at the Kaggle platform. As in the previous editions, the top three teams will be invited to present their solutions at a competition award session.
Prof Ana Carolina Lorena, Computer Science Professor at Instituto Tecnológico de Aeronáutica (ITA)
Prof Elaine Ribeiro de Faria, Computer Science Professor at Universidade Federal de Uberlândia (UFU)
Prof Filipe Alves Neto Verri, Computer Science Professor at Instituto Tecnológico de Aeronáutica (ITA)
Prof Marlo Souza, Universidade Federal da Bahia (UFBA)
Prof Ricardo Cerri, Computer Science Professor at Universidade Federal de São Carlos (UFSCar)
Prof Ricardo Rios, Computer Science Professor at Universidade Federal da Bahia (UFBA)
3rd KDD-BR (Brazilian Knowledge Discovery in Databases) competition:
Auto scoring of molecular marker clusters
Salvador, BA, Brazil, October 15 - 18, 2019
The 3rd KDD-BR (Brazilian Knowledge Discovery in Databases) competition is one of the joint activities of the 2019 editions of BRACIS and ENIAC.
The competition involves predicting the the similiarity between the partitions produced by the manual clustering of a set of molecular markers and those obtained by an auto-clustering tool. An auto-clustered scatterplot that is identical to its manual clustered counterpart receives a score of 1, while an auto-clustered scatterplot that is completely non-identical to its manual counterpart receives a 0 score. The dataset was provided by the Corteva Agriscience company.
The top three teams will be invited to present their solutions at a competition award session at the BRACIS 2019 conference.
Important Information:
Organizers (alphabetical order)
Ana Carolina Lorena, Computer Science Professor at Instituto Tecnológico de Aeronáutica (ITA)
Eduardo de Paula Costa, Associate Research Scientist at Corteva Agriscience
Elaine Ribeiro de Faria, Computer Science Professor at Universidade Federal de Uberlândia (UFU)
Filipe Alves Neto Verri, Computer Science Professor at Instituto Tecnológico de Aeronáutica (ITA)
Ricardo Araújo Rios, Computer Science Professor at Universidade Federal da Bahia (UFBA)
Ricardo Cerri, Computer Science Professor at Universidade Federal de São Carlos (UFSCar)
Please check our marketing proposal here and contact us through the e-mail bracis2019@ufba.br