Tomás Kliegr - RankMe

76 papers A 2B 5C 1Journal 31Unranked 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Meaningless is better: Hashing bias-inducing words in LLM prompts improves performance in logical reasoning and statistical learning. Inf. Process. Manag. Milena Chadimová, Eduard Jurásek, Tomás Kliegr
2026	J	`jnl`	qCBA: An R Package for Postoptimization of Rule Models Learnt on Quantized Data. R J. Tomás Kliegr
2025	—	`ed.`	Companion Proceedings of the 9th International Joint Conference on Rules and Reasoning, RuleML+RR 2025, also co-located with 21th Reasoning Web Summer School, RW 2025, and 17th DecisionCAMP 2025 as part of Declarative AI 2025, Istanbul, Türkiye, September 22-24, 2025. RuleML+RR (Companion) Alessandro Margara, Tomás Kliegr, Ognjen Savkovic, Shqiponja Ahmetaj, Riccardo Tommasini, Luigi Bellomarini, Evgeny Kharlamov, Ioana Georgiana Ciuciu, Dumitru Roman, George Konstantinidis, Emanuel Sallinger, Ahmet Soylu
2025	J	`jnl`	Explaining word embeddings with perfect fidelity: a case study in predicting research impact. Mach. Learn. Lucie Dvorackova, Marcin P. Joachimiak, Michal Cerny, Adriana Kubecova, Vilém Sklenák, Tomás Kliegr
2025	J	`jnl`	LLM-based feature generation from text for interpretable machine learning. Mach. Learn. Vojtech Balek, Lukás Sýkora, Vilém Sklenák, Tomás Kliegr
2025	J	`jnl`	Traceable LLM-based validation of statements in knowledge graphs. Inf. Process. Manag. Daniel Adam, Tomás Kliegr
2025	J	`jnl`	action-rules: GPU-accelerated Python package for counterfactual explanations and recommendations. SoftwareX Lukás Sýkora, Tomás Kliegr
2024	—	`ed.`	Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part I ECAI Workshops (1) Slawomir Nowaczyk, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova
2024	—	`ed.`	Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part II ECAI Workshops (2) Slawomir Nowaczyk, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova
2024	J	`jnl`	Explainable and interpretable machine learning and data mining. Data Min. Knowl. Discov. Martin Atzmueller, Johannes Fürnkranz, Tomás Kliegr, Ute Schmid
2024	J	`jnl`	Explaining word embeddings with perfect fidelity: Case study in research impact prediction. CoRR Lucie Dvorackova, Marcin P. Joachimiak, Michal Cerny, Adriana Kubecova, Vilém Sklenák, Tomás Kliegr
2024	J	`jnl`	LLM-based feature generation from text for interpretable machine learning. CoRR Vojtech Balek, Lukás Sýkora, Vilém Sklenák, Tomás Kliegr
2024	J	`jnl`	Meaningless is better: hashing bias-inducing words in LLM prompts improves performance in logical reasoning and statistical learning. CoRR Milena Chadimová, Eduard Jurásek, Tomás Kliegr
2024	J	`jnl`	Neurosymbolic Methods for Rule Mining. CoRR Agnieszka Lawrynowicz, Luis Galárraga, Mehwish Alam, Berenice Jaulmes, Vaclav Zeman, Tomás Kliegr
2024	J	`jnl`	Traceable LLM-based validation of statements in knowledge graphs. CoRR Daniel Adam, Tomás Kliegr
2023	B	`conf`	Apriori Modified for Action Rules Mining. K-CAP Lukás Sýkora, Tomás Kliegr
2023	J	`jnl`	Introduction to the Special Issue on Logic Rules and Reasoning: Selected Papers from the 4th International Joint Conference on Rules and Reasoning (RuleML+RR 2020). Theory Pract. Log. Program. Tomás Kliegr, Víctor Gutiérrez-Basulto, Ahmet Soylu
2023	—	`ed.`	Proceedings of the 17th International Rule Challenge and 7th Doctoral Consortium @ RuleML+RR 2023 co-located with 19th Reasoning Web Summer School (RW 2023) and 15th DecisionCAMP 2023 as part of Declarative AI 2023, Oslo, Norway, 18 - 20 September, 2023. RuleML+RR (Companion) Jan Vanthienen, Tomás Kliegr, Paul Fodor, Davide Lanti, Dörthe Arndt, Egor V. Kostylev, Theodoros Mitsikas, Ahmet Soylu
2023	J	`jnl`	QCBA: improving rule classifiers learned from quantitative data by recovering information lost by discretisation. Appl. Intell. Tomás Kliegr, Ebroul Izquierdo
2022	J	`jnl`	Explainability of Text Clustering Visualizations - Twitter Disinformation Case Study. IEEE Computer Graphics and Applications Jirí Zárský, Gaetan Lopez, Tomás Kliegr
2022	—	`conf`	High-Utility Action Rules Mining. RuleML+RR (Companion) Lukás Sýkora, Tomás Kliegr, Katerina Hrudková
2022	J	`jnl`	Why was this cited? Explainable machine learning applied to COVID-19 research literature. Scientometrics Lucie Beranová, Marcin P. Joachimiak, Tomás Kliegr, Gollam Rabby, Vilém Sklenák
2021	J	`jnl`	A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. Artif. Intell. Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
2021	—	`ed.`	Proceedings of the First International Workshop on Explainable and Interpretable Machine Learning (XI-ML 2020) co-located with the 43rd German Conference on Artificial Intelligence (KI 2020), Bamberg, Germany, September 21, 2020 (Virtual Workshop). XI-ML@KI Martin Atzmüller, Tomás Kliegr, Ute Schmid
2021	J	`jnl`	RDFRules: Making RDF rule mining easier and even more efficient. Semantic Web Václav Zeman, Tomás Kliegr, Vojtech Svátek
2020	—	`conf`	Action Rules: Counterfactual Explanations in Python. RuleML+RR (Supplement) Lukás Sýkora, Tomás Kliegr
2020	J	`jnl`	Editable machine learning models? A rule-based framework for user studies of explainability. Adv. Data Anal. Classif. Stanislav Vojír, Tomás Kliegr
2020	J	`jnl`	On cognitive preferences and the plausibility of rule-based models. Mach. Learn. Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
2020	B	`ed.`	Rules and Reasoning - 4th International Joint Conference, RuleML+RR 2020, Oslo, Norway, June 29 - July 1, 2020, Proceedings RuleML+RR Víctor Gutiérrez-Basulto, Tomás Kliegr, Ahmet Soylu, Martin Giese, Dumitru Roman
2019	J	`jnl`	Advances in Machine Learning for the Behavioral Sciences. CoRR Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
2019	J	`jnl`	Associative Classification in R: arc, arulesCBA, and rCBA. R J. Michael Hahsler, Ian Johnson, Tomás Kliegr, Jaroslav Kuchar
2019	—	`conf`	PyIDS - Python Implementation of Interpretable Decision Sets Algorithm by Lakkaraju et al, 2016. RuleML+RR (Supplement) Jirí Filip, Tomás Kliegr
2019	—	`conf`	Tuning Hyperparameters of Classification Based on Associations (CBA). ITAT Tomás Kliegr, Jaroslav Kuchar
2018	J	`jnl`	A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. CoRR Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
2018	J	`jnl`	Antonyms are similar: Towards paradigmatic association approach to rating similarity in SimLex-999 and WordSim-353. Data Knowl. Eng. Tomás Kliegr, Ondrej Zamazal
2018	—	`conf`	Classification based on Associations (CBA) - A Performance Analysis. RuleML+RR (Supplement) Jirí Filip, Tomás Kliegr
2018	J	`jnl`	EasyMiner.eu: Web framework for interpretable machine learning based on rules and frequent itemsets. Knowl. Based Syst. Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr
2018	J	`jnl`	On Cognitive Preferences and the Interpretability of Rule-based Models. CoRR Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
2018	—	`conf`	RdfRules Preview: Towards an Analytics Engine for Rule Mining in RDF Knowledge Graphs. RuleML+RR (Supplement) Vaclav Zeman, Tomás Kliegr, Vojtech Svátek
2018	B	`conf`	The Need for Interpretability Biases. IDA Johannes Fürnkranz, Tomás Kliegr
2017	—	`conf`	EasyMiner - Short History of Research and Current Development. ITAT Tomás Kliegr, Jaroslav Kuchar, Stanislav Vojír, Václav Zeman
2017	—	`—`	Effect of cognitive biases on human understanding of rule-based machine learning models. Tomás Kliegr
2017	J	`jnl`	InBeat: JavaScript recommender system supporting sensor input and linked data. Knowl. Based Syst. Jaroslav Kuchar, Tomás Kliegr
2017	—	`conf`	Outlier (Anomaly) Detection Modelling in PMML. RuleML+RR (Supplement) Jaroslav Kuchar, Adam Ashenfelter, Tomás Kliegr
2017	J	`jnl`	Quantitative CBA: Small and Comprehensible Association Rule Classification Models. CoRR Tomás Kliegr
2017	—	`conf`	Using EasyMiner API for Financial Data Analysis in the OpenBudgets.eu Project. RuleML+RR (Supplement) Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr
2016	B	`conf`	Crowdsourced Corpus with Entity Salience Annotations. LREC Milan Dojchinovski, Dinesh Reddy, Tomás Kliegr, Tomas Vitvar, Harald Sack
2016	J	`jnl`	LHD 2.0: A text mining approach to typing entities in knowledge graphs. J. Web Semant. Tomás Kliegr, Ondrej Zamazal
2015	—	`conf`	A Brief Overview of Rule Learning. RuleML Johannes Fürnkranz, Tomás Kliegr
2015	—	`conf`	Benchmark of Rule-Based Classifiers in the News Recommendation Task. CLEF Tomás Kliegr, Jaroslav Kuchar
2015	—	`conf`	EasyMiner/R Preview: Towards a Web Interface for Association Rule Learning and Classification in R. Challenge+DC@RuleML Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr
2015	J	`jnl`	Linked hypernyms: Enriching DBpedia with Targeted Hypernym Discovery. J. Web Semant. Tomás Kliegr
2015	—	`ch.`	Multimodal Fusion: Combining Visual and Textual Cues for Concept Detection in Video. Multimedia Data Mining and Analytics Damianos Galanopoulos, Milan Dojchinovski, Krishna Chandramouli, Tomás Kliegr, Vasileios Mezaris
2015	—	`ed.`	Proceedings of the RuleML 2015 Challenge, the Special Track on Rule-based Recommender Systems for the Web of Data, the Special Industry Track and the RuleML 2015 Doctoral Consortium hosted by the 9th International Web Rule Symposium (RuleML 2015), Berlin, Germany, August 2-5, 2015. Challenge+DC@RuleML Nick Bassiliades, Paul Fodor, Adrian Giurca, Georg Gottlob, Tomás Kliegr, Grzegorz J. Nalepa, Monica Palmirani, Adrian Paschke, Mark Proctor, Dumitru Roman, Fariba Sadri, Nenad Stojanovic
2014	—	`conf`	Business Rule Learning with Interactive Selection of Association Rules. Challenge+DC@RuleML Stanislav Vojír, Premysl Václav Duben, Tomás Kliegr
2014	—	`conf`	InBeat: Recommender System as a Service. CLEF (Working Notes) Jaroslav Kuchar, Tomás Kliegr
2014	—	`conf`	Learning Business Rules with Association Rule Classifiers. RuleML Tomás Kliegr, Jaroslav Kuchar, Davide Sottara, Stanislav Vojír
2014	A	`conf`	Orwellian Eye: Video Recommendation with Microsoft Kinect. ECAI Tomás Kliegr, Jaroslav Kuchar
2014	B	`conf`	Towards Linked Hypernyms Dataset 2.0: complementing DBpedia with hypernym discovery. LREC Tomás Kliegr, Ondrej Zamazal
2013	—	`conf`	Datasets, GATE Evaluation Framework for Benchmarking Wikipedia-Based NER Systems. NLP-DBPEDIA@ISWC Milan Dojchinovski, Tomás Kliegr
2013	—	`conf`	Entityclassifier.eu: Real-Time Classification of Entities in Text with Wikipedia. ECML/PKDD (3) Milan Dojchinovski, Tomás Kliegr
2013	A	`conf`	GAIN: web service for user tracking and preference learning - a smart TV use case. RecSys Jaroslav Kuchar, Tomás Kliegr
2013	—	`conf`	KINterestTV - Towards Non-invasive Measure of User Interest While Watching TV. eNTERFACE Julien Leroy, François Rocca, Matei Mancas, Radhwan Ben Madhkour, Fabien Grisard, Tomás Kliegr, Jaroslav Kuchar, Jakub Vit, Ivan Pirner, Petr Zimmermann
2013	—	`conf`	Transforming Association Rules to Business Rules: EasyMiner meets Drools. RuleML (2) Stanislav Vojír, Tomás Kliegr, Andrej Hazucha, Radek Skrabal, Milan Simunek
2013	—	`conf`	Wikipedia Search as Effective Entity Linking Algorithm. TAC Milan Dojchinovski, Ivo Lasek, Tomás Kliegr, Ondrej Zamazal
2012	—	`conf`	Association Rule Mining Following the Web Search Paradigm. ECML/PKDD (2) Radek Skrabal, Milan Simunek, Stanislav Vojír, Andrej Hazucha, Tomás Marek, David Chudán, Tomás Kliegr
2012	—	`conf`	Contextualised user profiling in networked media environments. UMAP Workshops Dorothea Tsatsou, Lyndon J. B. Nixon, Matei Mancas, Miroslav Vacura, Rüdiger Klein, Julien Leroy, Jaroslav Kuchar, Tomás Kliegr, Manuel Kober, Maria Loli, Vasileios Mezaris
2011	—	`conf`	Automated matching of data mining dataset schemata to background knowledge. OM Stanislav Vojír, Tomás Kliegr, Vojtech Svátek, Ondrej Sváb-Zamazal
2011	—	`conf`	Instant Feedback on Discovered Association Rules with PMML-Based Query-by-Example. RR Tomás Kliegr, Andrej Hazucha, Tomás Marek
2011	J	`jnl`	SEWEBAR-CMS: semantic analytical report authoring for data mining results. J. Intell. Inf. Syst. Tomás Kliegr, Vojtech Svátek, Martin Ralbovský, Milan Simunek
2010	—	`conf`	An XML Format for Association Rule Models Based on the GUHA Method. RuleML Tomás Kliegr, Jan Rauch
2010	—	`conf`	Entity classification by bag of Wikipedia articles. PIKM Tomás Kliegr
2010	—	`conf`	SEWEBAR-CMS: A System for Postprocessing Data Mining Models. RuleML Challenge Tomás Kliegr, David Chudán, Andrej Hazucha, Jan Rauch
2009	C	`conf`	Semantic Analytical Reports: A Framework for Post-processing Data Mining Results. ISMIS Tomás Kliegr, Martin Ralbovský, Vojtech Svátek, Milan Simunek, Vojtech Jirkovský, Jan Nemrava, Jan Zemánek
2009	—	`conf`	Towards semantic tagging in collaborative environments. DPS Krishna Chandramouli, Tomás Kliegr, Vojtech Svátek, Ebroul Izquierdo
2008	—	`conf`	Semantic annotation and linking of competitive intelligence reports for business clusters. OBI Jan Nemrava, Tomás Kliegr, Vojtech Svátek, Martin Ralbovský, Jirí Splíchal, Tomás Vejlupek