Work accepted for a symposium

18 de setembro de 2017

The work “A deep learning approach to prioritize customer service using social networks”, written by Paulo Amora, Elvis Teixeira, Gabriel Maia, Isabel Lima and Javam Machado, was accepted for the 5th Symposium on Knowledge Discovery, Mining and Learning (KDMiLe), which will occur in Uberlândia.

According to one of the researchers, Paulo Amora, “the work investigates how the Sentimental Analysis strategy can assist customer service by manifestations in social media. In addition to proposing a strategy for identifying urgent claims, it compares several machine learning techniques for this application”.

KDMiLe, which focuses on data mining and machine learning, has been taking place concomitantly with Simpósio Brasileiro de Banco de Dados (SBBD), the Brazilian Database Symposium (SBBD), since 2013. Articles are evaluated for their originality, relevance, technique and clarity of presentation.