Fourth special issue on knowledge discovery and business intelligence

[Excerpt] Expert Systems (ES) are a core element of human decision making. Initially, in the 70s and 80s, ES were focused on extracting explicit knowledge from human experts. With the availability of big data, after the 2000s, ES incorporated data-driven models, thus being associated with business intelligence, big data, data science and machine learning systems [Cortez and Santos, 2017]. The importance of data-driven models in the ES area is confirmed by the recent Wiley’s Expert Systems (EXSY) literature survey that analyzed all journal research articles published from 2000 to 2016 [Cortez et al., 2018]. The survey revealed data-driven as the most prevalent ES method type, corresponding to around 35% of all recently published EXSY papers. [...]We would like to thank the other KDBI 2017 track (of EPIA) co-organizers: Albert Bifet, Luis Cavique, and Nuno Marques. Also, we thank the authors, who contributed with their papers, and the reviewers (from the KDBI 2017 program committee and the EXSY journal). This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013