Selected DSXAI team publications (2020-now)
Back to the DSXAI team page
2024
- Martin Atzmueller, Johannes Fürnkranz, Tomáš Kliegr, Ute Schmid: Explainable and interpretable machine learning and data mining. Data Min. Knowl. Discov. 38(5): 2571-2595 (2024)
- Petr Máša, Jan Rauch: A novel algorithm for mining couples of enhanced association rules based on the number of output couples and its application. J. Intell. Inf. Syst. 62(2): 431-458 (2024)
- Petr Máša, Jan Rauch: A novel algorithm weighting different importance of classes in enhanced association rules. Knowl. Based Syst. 294: 111741 (2024)
2023
- Tomás Kliegr, Ebroul Izquierdo: QCBA: improving rule classifiers learned from quantitative data by recovering information lost by discretisation. Appl. Intell. 53(18): 20797-20827 (2023)
- Pavel Strnad, Lukás Švarc, Petr Berka: Synthetic dataset generator for anomaly detection in a university environment. Intell. Data Anal. 27(2): 417-422 (2023)
- Vojtěch Svátek, Ondřej Zamazal, Viet Bach Nguyen, Jiří Ivánek, Ján Kluka, Miroslav Vacura: Focused categorization power of ontologies: General framework and study on simple existential concept expressions. Semantic Web 14(6): 1209-1253 (2023)
- Viet Bach Nguyen, Vojtech Svátek: Pattern-based detection, extraction and analysis of code lists in ontologies and vocabularies. J. Web Semant. 77: 100788 (2023)
- Gollam Rabby, Petr Berka: Multi-class classification of COVID-19 documents using machine learning algorithms. J. Intell. Inf. Syst. 60(2): 571-591 (2023)
- Gollam Rabby, Jennifer D’Souza, Allard Oelen, Lucie Dvorackova, Vojtech Svátek, Sören Auer: Impact of COVID-19 research: a study on predicting influential scholarly documents using machine learning and a domain-independent knowledge graph. J. Biomed. Semant. 14(1): 18 (2023)
- Lukas Sykora, Tomás Kliegr: Apriori Modified for Action Rules Mining. K-CAP 2023: 30-34
2022
- Rauch, J., Šimůnek, M., Chudán, D., Máša, P.: Mechanising Hypothesis Formation – Principles and Case Studies. CRC Press (2022).
- Jirí Zárský, Gaetan Lopez, Tomás Kliegr: Explainability of Text Clustering Visualizations – Twitter Disinformation Case Study. IEEE Computer Graphics and Applications 42(4): 8-19 (2022)
- Lucie Beranová, Marcin P. Joachimiak, Tomás Kliegr, Gollam Rabby, Vilém Sklenák: Why was this cited? Explainable machine learning applied to COVID-19 research literature. Scientometrics 127(5): 2313-2349 (2022)
- Vojtech Svátek, Anna Nesterova, Viet Bach Nguyen: Quasi-Equivalent Concept Trade-Off in Ontology Design: Initial Considerations and Analyses. EKAW 2022: 209-216
2021
- Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz: A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. Artif. Intell. 295: 103458 (2021)
- Václav Zeman, Tomás Kliegr, Vojtech Svátek: RDFRules: Making RDF rule mining easier and even more efficient. Semantic Web 12(4): 569-602 (2021)
- Vojtech Svátek, Ján Kluka, Miroslav Vacura, Martin Homola, Marek Dudás: Patterns for Referring to Multiple Indirectly Specified Objects (MISO): Analysis and Guidelines. WOP (Book) 2021: 1-24
- Viet Bach Nguyen, Vojtech Svátek, Marek Dudás, Óscar Corcho: Knowledge Engineering of PhD Stories: A Preliminary Study. K-CAP 2021: 281-284
2020
- Stanislav Vojír, Tomás Kliegr: Editable machine learning models? A rule-based framework for user studies of explainability. Adv. Data Anal. Classif. 14(4): 785-799 (2020)
- Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim: On cognitive preferences and the plausibility of rule-based models. Mach. Learn. 109(4): 853-898 (2020)
- Petr Berka: Sentiment analysis using rule-based and case-based reasoning. J. Intell. Inf. Syst. 55(1): 51-66 (2020)
- Ondrej Zamazal: A Survey of Ontology Benchmarks for Semantic Web Ontology Tools. Int. J. Semantic Web Inf. Syst. 16(1): 47-68 (2020)
- Lu Zhou, Élodie Thiéblin, Michelle Cheatham, Daniel Faria, Catia Pesquita, Cássia Trojahn dos Santos, Ondrej Zamazal: Towards evaluating complex ontology alignments. Knowl. Eng. Rev. 35: e21 (2020)
- Élodie Thiéblin, Michelle Cheatham, Cássia Trojahn, Ondrej Zamazal: A consensual dataset for complex ontology matching evaluation. Knowl. Eng. Rev. 35: e34 (2020)
- Martin Homola, Ján Kluka, Petra Hozzová, Vojtech Svátek, Miroslav Vacura: Towards Higher-order OWL. Künstliche Intell. 34(3): 417-421 (2020)
- Viet Bach Nguyen, Vojtech Svátek, Gollam Rabby, Óscar Corcho: Ontologies Supporting Research-Related Information Foraging Using Knowledge Graphs: Literature Survey and Holistic Model Mapping. EKAW 2020: 88-103