| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |
|---|---|---|---|---|---|---|
| 17 | Yapicioglu F.R., Rigenti A., Cisci A., Aksoy M., Vitali F., Longo L. | Residual Value Prediction in Automotive: A Review of Methods and Data with Research Roadmap | IEEE Access | 2026 |
| Residual Value Prediction •
Artificial Intelligence •
Explainability •
Uncertainty Quantification |
| 16 | Nakanishi T. Longo L. | Approximate-Inverse Explainability of beta–VAE Latents for Multichannel EEG Participant-generalised Topographical Representation Learning | IEEE Access | 2025 |
@ARTICLE{NakanishiLongo2025, author={Nakanishi, Takafumi and Longo, Luca}, journal={IEEE Access}, title={Approximate-Inverse Explainability of ?–VAE Latents for Multichannel EEG Participant-Generalised Topographical Representation Learning}, year={2025}, volume={13}, number={}, pages={204773-204795}, keywords={Electroencephalography;Brain modeling;Spatial coherence;Scalp;Perturbation methods;Computational modeling;Explainable AI;Deep learning;Visualization;Videos;Electroencephalography (EEG);?–VAE;topographic mapping;explainable AI (XAI);approximate inverse model explanations (AIME);generative deep learning;representation learning}, doi={10.1109/ACCESS.2025.3635543}} [Close]
| Electroencephalography • Brain modeling • Spatial coherence • Scalp • Perturbation methods • Computational modeling • Explainable AI • Deep learning • Electroencephalography • VAE • topographic mapping • approximate inverse model explanations • generative deep learning • representation learning |
| 15 | Ephrem Tibebe Mekonnen; Longo L., Dondio P. | LOMATCE: LOcal Model-Agnostic Time-series Classification Explanations | IEEE Access | 2025 | @ARTICLE{MekonnenLongo2025, author={Mekonnen, Ephrem Tibebe and Longo, Luca and Dondio, Pierpaolo}, journal={IEEE Access}, title={LOMATCE: LOcal Model-Agnostic Time-series Classification Explanations}, year={2025}, volume={}, number={}, pages={1-1}, keywords={Time series analysis;Adaptation models;Explainable AI;Predictive models;Data models;Closed box;Perturbation methods;Computational modeling;Deep learning;Kernel;Explainable Artificial Intelligence;Model-agnostic;Time series;Post hoc;Deep learning;XAI}, doi={10.1109/ACCESS.2025.3625442}} [Close]
| Time series analysis • Adaptation models • Explainable AI • Predictive models • Data models • Closed box • Perturbation methods • Computational modeling • Deep learning • Kernel • Explainable Artificial Intelligence • Model-agnostic • Time series • Post hoc • Deep learning • XAI |
| 14 | Kopanja M., Savic M., Longo L. | CORTEX: Cost-Sensitive Rule and Tree Extraction Method | Knowledge-Based Systems | 2025 |
@article{KOPANJALongo2025, title = {CORTEX: Cost-Sensitive Rule and Tree Extraction Method}, journal = {Knowledge-Based Systems}, pages = {114592}, year = {2025}, issn = {0950-7051}, doi = {https://doi.org/10.1016/j.knosys.2025.114592}, url = {https://www.sciencedirect.com/science/article/pii/S0950705125016314}, } [Close]
| Explainable artificial intelligence •
Rule-based methods •
Tree-based methods •
Cost-sensitive decision tree •
Rule extraction •
Surrogate models |
| 13 | Manzoor A. Atif Qureshi M., KidneyE., Longo L. | A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners | IEEE Access | 2024 |
@ARTICLE{10531735, author={Manzoor, Awais and Qureshi, M. Atif and Kidney, Etain and Longo, Luca}, journal={IEEE Access}, title={A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners}, year={2024}, volume={}, number={}, pages={1-1}, keywords={Business;Predictive models;Switches;Reviews;Machine learning;Surveys;Profitability;Churn Prediction;Machine Learning;Artificial Intelligence;Business Decision making;Customer Defection;Marketing Analytics;Business Intelligence}, doi={10.1109/ACCESS.2024.3402092}} @ARTICLE{10531735, author={Manzoor, Awais and Qureshi, M. Atif and Kidney, Etain and Longo, Luca}, journal={IEEE Access}, title={A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners}, year={2024}, volume={}, number={}, pages={1-1}, keywords={Business;Predictive models;Switches;Reviews;Machine learning;Surveys;Profitability;Churn Prediction;Machine Learning;Artificial Intelligence;Business Decision making;Customer Defection;Marketing Analytics;Business Intelligence}, doi={10.1109/ACCESS.2024.3402092}} [Close]
| Churn Prediction • Machine Learning • Artificial Intelligence • Business Decision making • Customer Defection • Marketing Analytics • Business Intelligence • Business • Predictive models • Switches • Reviews • Machine learning • Surveys • Profitability |
| 12 | Raufi B., Longo L. | Comparing ANOVA and PowerShap Feature Selection Methods via Shapley Additive Explanations of Models of Mental Workload Built with the Theta and Alpha EEG Band Ratios | BioMedInformatics | 2024 |
@Article{biomedinformatics4010048, AUTHOR = {Raufi, Bujar and Longo, Luca}, TITLE = {Comparing ANOVA and PowerShap Feature Selection Methods via Shapley Additive Explanations of Models of Mental Workload Built with the Theta and Alpha EEG Band Ratios}, JOURNAL = {BioMedInformatics}, VOLUME = {4}, YEAR = {2024}, NUMBER = {1}, PAGES = {853--876}, URL = {https://www.mdpi.com/2673-7426/4/1/48}, ISSN = {2673-7426}, DOI = {10.3390/biomedinformatics4010048} } [Close]
| model explainability • mental workload • statistical feature selection • Shapley-based feature selection • alpha and theta EEG band ratios • machine learning • Deep-learning |
| 11 | Gómez Tapia C., Bozic B., Longo L. | Investigating the Effect of Pre-processing Methods on Model Decision-Making in EEG-Based Person Identification | eXplainable Artificial Intelligence, The World Conference (xAI-2023) | 2023 |
@InProceedings{GomezLongo2023, author="Tapia, Carlos G{\'o}mez and Bozic, Bojan and Longo, Luca", editor="Longo, Luca", title="Investigating the Effect of Pre-processing Methods on Model Decision-Making in EEG-Based Person Identification", booktitle="Explainable Artificial Intelligence", year="2023", publisher="Springer Nature Switzerland", address="Cham", pages="131--152", isbn="978-3-031-44070-0" } [Close]
| Electroencephalography •
eXplainable Artificial Intelligence •
Deep Learning •
Signal processing •
attribution xAI methods •
Graph-Neural Network •
Biometrics •
signal-to-noise ratio |
| 10 | Vilone G., Longo L. | Development of a Human-Centred Psychometric Test for the Evaluation of Explanations Produced by XAI Methods | eXplainable Artificial Intelligence, The World Conference (xAI-2023) | 2023 | @InProceedings{ViloneLongo2023, author="Vilone, Giulia and Longo, Luca", editor="Longo, Luca", title="Development of a Human-Centred Psychometric Test for the Evaluation of Explanations Produced by XAI Methods", booktitle="Explainable Artificial Intelligence", year="2023", publisher="Springer Nature Switzerland", address="Cham", pages="205--232", isbn="978-3-031-44070-0" } [Close]
| Explainable Artificial Intelligence • Human-centred evaluation • Psychometrics • Machine Learning • Deep Learning • Explainability |
| 9 | Vilone G., Longo L. | A Quantitative Evaluation of Global, Rule-Based Explanations of Post-Hoc, Model Agnostic Methods | Frontiers in Artificial Intelligence | 2021 |
@ARTICLE{ViloneLongo2021, AUTHOR={Vilone, Giulia and Longo, Luca}, TITLE={A Quantitative Evaluation of Global, Rule-Based Explanations of Post-Hoc, Model Agnostic Methods}, JOURNAL={Frontiers in Artificial Intelligence}, VOLUME={4}, PAGES={160}, YEAR={2021}, URL={https://www.frontiersin.org/article/10.3389/frai.2021.717899}, DOI={10.3389/frai.2021.717899}, ISSN={2624-8212} } [Close]
| explainable artificial intelligence • rule extraction • method comparison and evaluation • metrics of
explainability • method automatic ranking • artificial intelligence • explainability |
| 8 | Vilone G., Longo L. | Classification of Explainable Artificial Intelligence Methods through Their Output Formats | Machine Learning and Knowledge Extraction | 2021 |
@Article{Vilone2021Output, AUTHOR = {Vilone, Giulia and Longo, Luca}, TITLE = {Classification of Explainable Artificial Intelligence Methods through Their Output Formats}, JOURNAL = {Machine Learning and Knowledge Extraction}, VOLUME = {3}, YEAR = {2021}, NUMBER = {3}, PAGES = {615--661}, URL = {https://www.mdpi.com/2504-4990/3/3/32}, ISSN = {2504-4990}, DOI = {10.3390/make3030032} } [Close]
| explainable artificial intelligence • method classification • systematic literature review |
| 7 | Vilone G, Longo L. | Notions of explainability and evaluation approaches for explainable artificial intelligence | Information fusion | 2021 |
@article{VILONE202189, title = {Notions of explainability and evaluation approaches for explainable artificial intelligence}, journal = {Information Fusion}, volume = {76}, pages = {89-106}, year = {2021}, issn = {1566-2535}, doi = {https://doi.org/10.1016/j.inffus.2021.05.009}, url = {https://www.sciencedirect.com/science/article/pii/S1566253521001093}, author = {Giulia Vilone and Luca Longo}, keywords = {Explainable artificial intelligence, Notions of explainability, Evaluation methods}, } [Close]
| Explainable artificial intelligence •
Notions of explainability •
Evaluation methods |
| 6 | Hancock, G. and Longo, L. and Hancock, P. and Young, M. | Mental Workload | Handbook of human factors & ergonomics | 2021 |
@incollection{HancockLongo2021, author = {Hancock, G. and Longo, L. and Hancock, P. and Young, M.}, title = {Mental workload}, booktitle = {Handbook of human factors & ergonomics}, edition = {5}, year = {2021}, chapter ={7}, editor = {Salvendy, G. and Karwalski, W.}, publisher ={Taylor \& Francis} } [Close]
| Mental Workload • Cognitive load • Techniques • methods |
| 5 | Vilone G., Rizzo L., Longo L. | A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence | Proceedings for the 28th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Ireland, December 7-8, 2020 | 2020 |
@inproceedings{DBLP:conf/aics/ViloneRL20, author = {Giulia Vilone and Lucas Rizzo and Luca Longo}, editor = {Luca Longo and Lucas Rizzo and Elizabeth Hunter and Arjun Pakrashi}, title = {A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence}, booktitle = {Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Republic of Ireland, December 7-8, 2020}, series = {{CEUR} Workshop Proceedings}, volume = {2771}, pages = {85--96}, publisher = {CEUR-WS.org}, year = {2020}, url = {http://ceur-ws.org/Vol-2771/AICS2020\_paper\_33.pdf} } [Close]
| Explainable artificial intelligence • Rule extraction • Method • comparison • evaluation |
| 4 | Orru G., Longo L. | Direct and Constructivist Instructional Design: A Comparison of Efficiency Using Mental Workload and Task Performance | 4th International Symposium on Human Mental Workload: Models and Applications | 2020 |
@InProceedings{10.1007/978-3-030-62302-9_7, author="Orru, Giuliano and Longo, Luca", editor="Longo, Luca and Leva, Maria Chiara", title="Direct and Constructivist Instructional Design: A Comparison of Efficiency Using Mental Workload and Task Performance", booktitle="Human Mental Workload: Models and Applications", year="2020", publisher="Springer International Publishing", address="Cham", pages="99--123", isbn="978-3-030-62302-9" } [Close]
| Cognitive load theory • Mental workload • Efficiency • Direct instruction methods • Inquiry methods |
| 3 | Longo L. | Empowering Qualitative Research Methods in Education with Artificial Intelligence | WCQR 2019: Computer Supported Qualitative Research | 2019 |
@InProceedings{Longo2019Empowering, author="Longo, Luca", editor="Costa, Ant{\'o}nio Pedro and Reis, Lu{\'i}s Paulo and Moreira, Ant{\'o}nio", title="Empowering Qualitative Research Methods in Education with Artificial Intelligence", booktitle="Computer Supported Qualitative Research", year="2020", publisher="Springer International Publishing", address="Cham", pages="1--21" } [Close]
| Artificial intelligence • Qualitative research Methods • Data analysis • Education • Teaching • Learning • Behaviourism • Constructivism • Cognitivism • Automated reasoning • Knowledge representation • Machine learning • Planning • Perception • Natural language processing |
| 2 | Longo L, Orru G. | An Evaluation of the Reliability, Validity and Sensitivity of Three Human Mental Workload Measures Under Different Instructional Conditions in Third-Level Education | McLaren B., Reilly R., Zvacek S., Uhomoibhi J. (eds) Computer Supported Education. CSEDU 2018. | 2019 |
@InProceedings{10.1007/978-3-030-21151-6_19, author="Longo, Luca and Orru, Giuliano", editor="McLaren, Bruce M. and Reilly, Rob and Zvacek, Susan and Uhomoibhi, James", title="An Evaluation of the Reliability, Validity and Sensitivity of Three Human Mental Workload Measures Under Different Instructional Conditions in Third-Level Education", booktitle="Computer Supported Education", year="2019", publisher="Springer International Publishing", address="Cham", pages="384--413", isbn="978-3-030-21151-6" } [Close]
| Cognitive Load Theory • Cognitive load types • Human Mental Workload • Instructional design • Direct instructions • Cognitive Theory of Multimedia Learning • Inquiry methods • Community of Inquiry • Reliability • Validity • Sensitivity • Education |
| 1 | Moustafa K., Luz S., Longo L. | Assessment of Mental Workload: A Comparison of Machine Learning Methods and Subjective Assessment Techniques | International Symposium on Human Mental Workload: Models and Applications | 2017 |
@inproceedings{moustafa2017assessment, title={Assessment of mental workload: a comparison of machine learning methods and subjective assessment techniques}, author={Moustafa, Karim and Luz, Saturnino and Longo, Luca}, booktitle={International Symposium on Human Mental Workload: Models and Applications}, pages={30--50}, year={2017}, organization={Springer} } [Close]
| Mental Workload • Machine Learning • Subjective assessment techniques • Modeling |
| # | Authors | Title | Details | Date | Pdf/Links/Bibtex | Keywords |