| Learning business rules with association rule classifiers T Kliegr, J Kuchař, D Sottara, S Vojíř Rules on the Web. From Theory to Applications: 8th International Symposium …, 2014 | 39 | 2014 |
| EasyMiner. eu: Web framework for interpretable machine learning based on rules and frequent itemsets S Vojíř, V Zeman, J Kuchař, T Kliegr Knowledge-Based Systems 150, 111-115, 2018 | 26 | 2018 |
| Editable machine learning models? A rule-based framework for user studies of explainability S Vojíř, T Kliegr Advances in Data Analysis and Classification 14 (4), 785-799, 2020 | 13 | 2020 |
| Transforming association rules to business rules: EasyMiner meets Drools S Vojır, T Kliegr, A Hazucha, R Škrabal, M Šimunek RuleML (2) 1004, 2013 | 11 | 2013 |
| Association rule mining following the web search paradigm R Škrabal, M Šimůnek, S Vojíř, A Hazucha, T Marek, D Chudán, T Kliegr Machine Learning and Knowledge Discovery in Databases: European Conference …, 2012 | 11 | 2012 |
| Towards re-decentralized future of the web: Privacy, security and technology development S Vojíř, J Kučera Acta Informatica Pragensia 10 (3), 349-369, 2021 | 9 | 2021 |
| Background knowledge and PMML: first considerations T Kliegr, S Vojíř, J Rauch Proceedings of the 2011 workshop on Predictive markup language modeling, 54-62, 2011 | 9 | 2011 |
| EasyMiner/R Preview: Towards a Web Interface for Association Rule Learning and Classification in R. S Vojír, V Zeman, J Kuchar, T Kliegr Challenge+ DC@ RuleML, 2015 | 8 | 2015 |
| Social and Technical Aspects of Re-decentralized web S Vojíř, Z Smutný, J Kučera IDIMT-2020 Digitalized Economy, Society and Information Management, 107-116, 2020 | 6 | 2020 |
| Elicitation of background knowledge for data mining J Balhar, T Kliegr, D Šťastný, S Vojíř Proceedings of Znalosti 2010, 167-170, 2010 | 6 | 2010 |
| EasyMiner-Short History of Research and Current Development. T Kliegr, J Kuchar, S Vojír, V Zeman ITAT 2017, 235-239, 2017 | 4 | 2017 |
| Business rules mining using GUHA method for the personalization of commercial offers S Vojir, Z Smutny Engineering Economics 28 (2), 215-224, 2017 | 4 | 2017 |
| Business rule learning with interactive selection of association rules S Vojır, PV Duben, T Kliegr RuleML Challenge 2014, 2014 | 4 | 2014 |
| A Methodology Concept of Online Marketing Management with a Knowledge Base of Interactions from Internet-based Services Z Smutny, S Vojir 3rd International Conference on Innovation and Entrepreneurship, 242-249, 2015 | 3 | 2015 |
| Can variants, reinfection, symptoms and test types affect COVID-19 diagnostic performance? A large-scale retrospective study of AG-RDTs during circulation of Delta and Omicron … T Kliegr, J Jarkovský, H Jiřincová, J Kuchař, T Karel, D Chudán, S Vojíř, ... Eurosurveillance 28 (38), 2200938, 2023 | 2 | 2023 |
| Using EasyMiner API for Financial Data Analysis in the OpenBudgets. eu Project S Vojíř, V Zeman, J Kuchař, T Kliegr Proceedings of the Doctoral Consortium, Challenge, Industry Track, Tutorials …, 2017 | 2 | 2017 |
| Využití EasyMiner API v projektu OpenBudgets. eu S Vojíř, V Zeman, J Kuchař, T Kliegr Západočeská univerzita v Plzni, 2017 | 1 | 2017 |
| Extension of Business Rule Sets Using Data Mining of GUHA Association Rules S Vojíř Proceedings of the 15th Conference ITAT, 59-64, 2015 | 1 | 2015 |
| Application of Semantic Network for Knowledge Sharing in the Field of Marketing S Vojir, Z Smutny European Conference on Knowledge Management 3, 1306, 2014 | 1 | 2014 |
| Transformation of GUHA association rules to business rules for implementation using JBoss Drools S Vojíř CEUR Workshop Proceedings. Information Technologies–Applications and Theory …, 2013 | 1 | 2013 |
Tomáš KliegrVysoká škola ekonomická v PrazeVerified email at vse.cz
