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
A KDBI special issue is already confirmed with the Expert Systems: The Journal of Knowledge Engineering (Clarivate JCR Impact Factor 2021: 2.812) for the extended versions of the best KDBI2022 papers. For further information, follow this link:
https://onlinelibrary.wiley.com/page/journal/14680394/homepage/call-for-papers/si-2023-000092


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.



Paper submission deadline April 16, 2023
Notification of paper acceptance May 9, 2023
Camera-ready papers deadline June 15, 2023
Conference dates September 5-8, 2023

The EPIA Conference on Artificial Intelligence (AI) is a well-established European conference in the field of AI. The 22nd edition of the EPIA conference will take place at Faial Island in the Azores Archipelago, from September 5th to September 8th, 2023.

As in previous editions, this international conference was hosted with the patronage of the Portuguese Association for Artificial Intelligence (APPIA). The purpose of the EPIA conference is to promote research in all areas of AI, covering both theoretical/foundational issues and applications, and the scientific exchange among researchers, engineers and practitioners in related disciplines.