Track Description

Information system development and management is increasingly benefiting from advances in Artificial Intelligence (AI). On the one hand, AI can provide robust approaches for software development, in order to analyze and evaluate complex software, its development processes, and its proper configuration.

Repository mining, machine learning, big data analytics, and visualization can enable targeted insights and powerful predictions for software quality, software development, and software project management. These techniques are nowadays used by large companies to perform all the steps necessary for software development (requirements, design, implementation, testing, or deployment) faster, better, and at a lower cost.

On the other hand, many information systems have components that use AI to cluster, classify, or predict. We refer here primarily to components that employ data science and machine learning methods in the analysis of tabular data, but we do not exclude components that use computer vision or natural language processing. These components are used in a variety of applications, changing how many industries perform and conduct their day-to-day operations, from manufacturing and logistics, to modernizing government, finance, and healthcare streams.

Track Chairs

Bruno Martins, University of Lisboa, Portugal
Diego Seco Naveiras, University of A Coruña, Spain

Papers

A Comparative Analysis of Open-Source Business Intelligence Platforms for Integration with a Low-Code Platform

David Aveiro, ARDITI - Regional Agency for the Development of Research & University of Madeira & NOVA-LINCS - Universidade NOVA de Lisboa, Funchal, Portugal
João Mendes, ARDITI - Regional Agency for the Development of Research & University of Madeira, Funchal, Portugal
Duarte Pinto, ARDITI - Regional Agency for the Development of Research, Funchal, Portugal
Vítor Freitas, ARDITI - Regional Agency for the Development of Research & University of Madeira, Funchal, Portugal

Cyclist Route Assessment Using Machine Learning

Alan Nunes Caetano, IADE, Universidade Europeia, Lisbon, Portugal
Jacinto Estima, Univ Coimbra, CISUC, Department of Informatics Engineering, Coimbra, Portugal
Edirlei Soares Lima, IADE, Universidade Europeia, Lisbon, Portugal

Data Exploration as a Trigger for Customer Relationship Management

Celina Maria Olszak, University of Economics in Katowice, Katowice, Poland
Marcin Jan Pałys, University of Economics in Katowice, Katowice, Poland

EEG To FMRI Synthesis: Is Deep Learning a Candidate?

David Calhas, INESC-ID Instituto Superior Técnico, Lisbon, Portugal
Rui Henriques, INESC-ID Instituto Superior Técnico, Lisbon, Portugal

Late Fusion Approach for Multimodal Emotion Recognition Based on Convolutional and Graph Neural Networks

Tomasz Wiercinski, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland
Teresa Zawadzka, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland

Neural Network Based Multi-Criteria Ranking Prediction - Sustainability Assessment Case Study

Jarosław Watróbski, University of Szczecin & National Institute of Telecommunications Szczecin, Warsaw, Poland
Aleksandra Baczkiewicz, University of Szczecin, Szczecin, Poland
Robert Król, University of Szczecin, Szczecin, Poland
Iga Rudawska, University of Szczecin, Szczecin, Poland

Scheme Selection Based on Clusters’ Quality in Multi-Clustering M − CCF Recommender System

Urszula Kuzelewska, Faculty of Computer Science/ Bialystok University of Technology, Bialystok, Poland

Streamlining Literature Reviews Using an Automatic and Flexible Data Gathering and Classification Platform

António Miguel Martins, INESC-ID, Instituto Superior Técnico, Universidade de Lisboa
Alberto Rodrigues da Silva, INESC-ID, Instituto Superior Técnico, Universidade de Lisboa
Jacinto Estima, CISUC, Dep. of Informatics Engineering, University of Coimbra & INESC-ID, Lisboa, Portugal

Time Series Classification Using Images: The Case Of SAX-Like Transformation

Miłosz Wrzesien, Faculty of Electrical Eng., Automatics, Computer Science and Biomedical Eng., AGH University of Science and Technology, Kraków, Poland
Mariusz Wrzesien, Faculty of Applied Information Technology, University of Information Technology and Management, Rzeszów, Poland
Władysław Homenda, Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland & Faculty of Applied Information Technology, University of Information Technology and Management, Rzeszów, Poland

Towards a Prescriptive Framework for Selecting Suitable Artificial Intelligence Algorithms for Enterprise-Level Problems

Prithvi Bhattacharya, University of Wollongong (in Dubai) Dubai, UAE