In this age of big data, business organizations moving towards decision-making processes that are based on data-driven models. Knowledge Discovery (KD) is a branch of Artificial Intelligence (AI) that aims to extract useful knowledge from complex or large volumes of data. Business Intelligence (BI) is an umbrella term that represents computer architectures, technologies and methods to enhance managerial decision-making. Both KD and BI are faced with new challenges, such as: Internet expansion, real-world with increasing dynamic and unstable environments, integration of expert knowledge into the data-driven learning, and better support of informed decisions. Several AI techniques can be used to address these problems, such as Machine Learning/Data Mining/Data Science, Evolutionary Computation and Modern Optimization, Forecasting, Neural Computing and Deep Learning.

The aim of this workshop is to gather the latest research in KD and BI. In particular, papers that describe experience and lessons learned from KD/BI projects, presenting business or end user impacts using AI technologies, are welcome.

Special Issue of the Journal Expert Systems

Authors of the best papers presented at the KDBI 2021 track of EPIA will be invited to submit extended versions of their manuscripts for a special issue KDBI of the ‘The Wiley-Blackwell Journal Expert Systems: The Journal of Knowledge Engineering’, indexed at ISI Web of Knowledge (ISI impact factor JCR 2019 1.546).

This special issue corresponds to the 6th KDBI special issue on Expert Systems (ES) journal (e.g., the 5th issue is available at: https://onlinelibrary.wiley.com/toc/14680394/2020/37/6 ).

Topics of Interest

A non-exhaustive list of topics of interest is defined as follows:

• Knowledge Discovery (KD)
  • Data Pre-Processing;
  • Intelligent Data Analysis;
  • Temporal and Spatial KD;
  • Data and Knowledge Visualization;
  • Machine Learning (e.g., Decision Trees, Neural Networks and Deep
    Learning, Bayesian Learning, Inductive and Fuzzy Logic);
  • Hybrid Learning Models and Methods: Using KD methods and Cognitive
    Models, Learning in Ontologies, inductive logic, etc.
  • Domain KD: Learning from Heterogeneous, Text and Multimedia data,
    Networks, Graphs and Link Analysis;
  • Data Mining tasks: Classification, Regression, Clustering and
    Association Rules;
  • Ubiquitous Data Mining: Distributed Data Mining, Incremental
    Learning, Change Detection, Learning from Ubiquitous Data Streams;
• Business Intelligence (BI)/Business Analytics/Data Science
  • Methodologies, Architectures or Computational Tools;
  • Artificial Intelligence (e.g., KD, Evolutionary Computation, Intelligent Agents, Logic) applied to BI: Data Warehouse, OLAP, Data Mining, Decision Support Systems, Dashboards, Business Analytics, Adaptive BI and Competitive Intelligence.
• Real-word Applications
  • Finance, Marketing, Banking, Medicine, Education, Industry and Services.
  • Big Data, Cloud Computing, Web Intelligence and Social Network Mining.

Organizing Committee

Paulo Cortez, University of Minho, Portugal
Albert Bifet, Université Paris-Saclay, France
Luís Cavique, Universidade Aberta, Portugal
João Gama, University of Porto, Portugal
Nuno Marques, New University of Lisbon, Portugal
Manuel Filipe Santos, University of Minho, Portugal

Program Committee

Agnes Braud, University of Strasbourg, France
Alberto Bugarin, University of Santiago de Compostela, Spain
Alipio M. Jorge, University of Porto, Portugal
Amilcar Oliveira, Universidade Aberta, Portugal
André Carvalho, University of São Paulo, Brazil
Antonio Tallón-Ballesteros, University of Huelva, Spain
Armando Mendes, University of Azores, Portugal
Carlos Ferreira, Institute of Eng. of Porto, Portugal
Fátima Rodrigues, Institute of Eng. of Porto, Portugal
João Moura-Pires, Univ. NOVA de Lisboa, Portugal
Jose Alfredo Ferreira Costa, University Rio Grande Norte, Brazil
Karin Becker, University Rio Grande Norte, Brazil
Leandro Krug Wives, University Rio Grande Sul, Brazil
Manuel Fernandez Delgado, University of Santiago de Compostela, Spain
Marcos Aurélio Domingues, State University of Maringá, Brazil
Margarida Cardoso, ISCTE-IUL, Portugal
Mark Embrechts, Rensselaer Polytechnic Institute, USA
Mohamed Gaber, Birmingham City University, UK
Murat Caner Testik, Hacettepe University, Turkey
Orlando Belo, University of Minho, Portugal
Pedro Castillo, University of Granada, Spain
Phillipe Lenca, IMT Atlantique, France
Rita Ribeiro, Universidade do Porto, Portugal
Roberto Henriques, New University of Lisbon, Portugal
Rui Camacho, University of Porto, Portugal
Sérgio Moro, ISCTE-IUL, Portugal
Ying Tan, Peking University, China