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: Digital Transformation, Internet-of-Things, Industry 4.0, Smart Cities, Increasing dynamic and unstable real-world environments, explainable AI (XAI) and better support of informed decisions. Several AI techniques can be used to address these problems, such as Machine Learning and Deep Learning, Data Mining, Data Science and Business Analytics, and Evolutionary Computation and Metaheuristics.

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.

JOURNAL TRACK

TOPICS OF INTEREST

Knowledge Discovery (KD):

• Data Pre-Processing
• Temporal and Spatial KD
• Explainable AI (XAI), Data and Knowledge Visualization
• Machine Learning (e.g., Decision Trees, Deep Learning, Ensembles)
• Data Mining tasks: Classification, Regression, Clustering and Association Rules, Process Mining, Learning from Text and Multimedia data, Graph Mining
• Data Streams and Distributed Data Mining

Business Intelligence (BI), Business Analytics and Data Science:

• Methodologies, Architectures or Computational Tools
• Artificial Intelligence (e.g., KD, Evolutionary Computation) 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.