Tomás Kliegr

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 29

Top Topics

Machine Learning

Top Venues

RuleML+RR (Supplement)

Knowl. Based Syst.

Publications

Tomás Kliegr, Ebroul Izquierdo
QCBA: improving rule classifiers learned from quantitative data by recovering information lost by discretisation. Appl. Intell. 53 (18) (2023)
Lukas Sykora, Tomás Kliegr
Apriori Modified for Action Rules Mining. K-CAP (2023)
Tomás Kliegr, Víctor Gutiérrez-Basulto, Ahmet Soylu
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. 23 (3) (2023)
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) (2022)
Jirí Zárský, Gaetan Lopez, Tomás Kliegr
Explainability of Text Clustering Visualizations - Twitter Disinformation Case Study. IEEE Computer Graphics and Applications 42 (4) (2022)
Lukas Sykora, Tomás Kliegr, Katerina Hrudková
High-Utility Action Rules Mining. RuleML+RR (Companion) (2022)
Václav Zeman, Tomás Kliegr, Vojtech Svátek
RDFRules: Making RDF rule mining easier and even more efficient. Semantic Web 12 (4) (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 (2021)
Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
On cognitive preferences and the plausibility of rule-based models. Mach. Learn. 109 (4) (2020)
Lukas Sykora, Tomás Kliegr
Action Rules: Counterfactual Explanations in Python. RuleML+RR (Supplement) (2020)
Stanislav Vojír, Tomás Kliegr
Editable machine learning models? A rule-based framework for user studies of explainability. Adv. Data Anal. Classif. 14 (4) (2020)
Jirí Filip, Tomás Kliegr
PyIDS - Python Implementation of Interpretable Decision Sets Algorithm by Lakkaraju et al, 2016. RuleML+RR (Supplement) (2019)
Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
Advances in Machine Learning for the Behavioral Sciences. CoRR (2019)
Michael Hahsler, Ian Johnson, Tomás Kliegr, Jaroslav Kuchar
Associative Classification in R: arc, arulesCBA, and rCBA. R J. 11 (2) (2019)
Tomás Kliegr, Jaroslav Kuchar
Tuning Hyperparameters of Classification Based on Associations (CBA). ITAT (2019)
Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim
On Cognitive Preferences and the Interpretability of Rule-based Models. CoRR (2018)
Johannes Fürnkranz, Tomás Kliegr
The Need for Interpretability Biases. IDA (2018)
Jirí Filip, Tomás Kliegr
Classification based on Associations (CBA) - A Performance Analysis. RuleML+RR (Supplement) (2018)
Tomás Kliegr, Ondrej Zamazal
Antonyms are similar: Towards paradigmatic association approach to rating similarity in SimLex-999 and WordSim-353. Data Knowl. Eng. 115 (2018)
Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz
A review of possible effects of cognitive biases on interpretation of rule-based machine learning models. CoRR (2018)
Vaclav Zeman, Tomás Kliegr, Vojtech Svátek
RdfRules Preview: Towards an Analytics Engine for Rule Mining in RDF Knowledge Graphs. RuleML+RR (Supplement) (2018)
Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr
EasyMiner.eu: Web framework for interpretable machine learning based on rules and frequent itemsets. Knowl. Based Syst. 150 (2018)
Tomás Kliegr
Quantitative CBA: Small and Comprehensible Association Rule Classification Models. CoRR (2017)
Tomás Kliegr, Jaroslav Kuchar, Stanislav Vojír, Václav Zeman
EasyMiner - Short History of Research and Current Development. ITAT (2017)
Jaroslav Kuchar, Adam Ashenfelter, Tomás Kliegr
Outlier (Anomaly) Detection Modelling in PMML. RuleML+RR (Supplement) (2017)
Jaroslav Kuchar, Tomás Kliegr
InBeat: JavaScript recommender system supporting sensor input and linked data. Knowl. Based Syst. 135 (2017)
Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr
Using EasyMiner API for Financial Data Analysis in the OpenBudgets.eu Project. RuleML+RR (Supplement) (2017)
Milan Dojchinovski, Dinesh Reddy, Tomás Kliegr, Tomas Vitvar, Harald Sack
Crowdsourced Corpus with Entity Salience Annotations. LREC (2016)
Tomás Kliegr, Ondrej Zamazal
LHD 2.0: A text mining approach to typing entities in knowledge graphs. J. Web Semant. 39 (2016)
Tomás Kliegr, Jaroslav Kuchar
Benchmark of Rule-Based Classifiers in the News Recommendation Task. CLEF (2015)
Johannes Fürnkranz, Tomás Kliegr
A Brief Overview of Rule Learning. RuleML (2015)
Tomás Kliegr
Linked hypernyms: Enriching DBpedia with Targeted Hypernym Discovery. J. Web Semant. 31 (2015)
Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr
EasyMiner/R Preview: Towards a Web Interface for Association Rule Learning and Classification in R. Challenge+DC@RuleML (2015)
Stanislav Vojír, Premysl Václav Duben, Tomás Kliegr
Business Rule Learning with Interactive Selection of Association Rules. Challenge+DC@RuleML (2014)
Tomás Kliegr, Jaroslav Kuchar, Davide Sottara, Stanislav Vojír
Learning Business Rules with Association Rule Classifiers. RuleML (2014)
Tomás Kliegr, Jaroslav Kuchar
Orwellian Eye: Video Recommendation with Microsoft Kinect. ECAI (2014)
Jaroslav Kuchar, Tomás Kliegr
InBeat: Recommender System as a Service. CLEF (Working Notes) (2014)
Tomás Kliegr, Ondrej Zamazal
Towards Linked Hypernyms Dataset 2.0: complementing DBpedia with hypernym discovery. LREC (2014)
Stanislav Vojír, Tomás Kliegr, Andrej Hazucha, Radek Skrabal, Milan Simunek
Transforming Association Rules to Business Rules: EasyMiner meets Drools. RuleML (2) (2013)
Jaroslav Kuchar, Tomás Kliegr
GAIN: web service for user tracking and preference learning - a smart TV use case. RecSys (2013)
Milan Dojchinovski, Tomás Kliegr
Datasets, GATE Evaluation Framework for Benchmarking Wikipedia-Based NER Systems. NLP-DBPEDIA@ISWC (2013)
Milan Dojchinovski, Ivo Lasek, Tomás Kliegr, Ondrej Zamazal
Wikipedia Search as Effective Entity Linking Algorithm. TAC (2013)
Milan Dojchinovski, Tomás Kliegr
Entityclassifier.eu: Real-Time Classification of Entities in Text with Wikipedia. ECML/PKDD (3) (2013)
Julien Leroy, François Rocca, Matei Mancas, Radhwan Ben Madhkour, Fabien Grisard, Tomás Kliegr, Jaroslav Kuchar, Jakub Vit, Ivan Pirner, Petr Zimmermann
KINterestTV - Towards Non-invasive Measure of User Interest While Watching TV. eNTERFACE (2013)
Dorothea Tsatsou, Lyndon J. B. Nixon, Matei Mancas, Miroslav Vacura, Rüdiger Klein, Julien Leroy, Jaroslav Kuchar, Tomás Kliegr, Manuel Kober, Maria Loli, Vasileios Mezaris
Contextualised user profiling in networked media environments. UMAP Workshops (2012)
Radek Skrabal, Milan Simunek, Stanislav Vojír, Andrej Hazucha, Tomás Marek, David Chudán, Tomás Kliegr
Association Rule Mining Following the Web Search Paradigm. ECML/PKDD (2) (2012)
Tomás Kliegr, Vojtech Svátek, Martin Ralbovský, Milan Simunek
SEWEBAR-CMS: semantic analytical report authoring for data mining results. J. Intell. Inf. Syst. 37 (3) (2011)
Tomás Kliegr, Andrej Hazucha, Tomás Marek
Instant Feedback on Discovered Association Rules with PMML-Based Query-by-Example. RR (2011)
Stanislav Vojír, Tomás Kliegr, Vojtech Svátek, Ondrej Sváb-Zamazal
Automated matching of data mining dataset schemata to background knowledge. OM (2011)
Tomás Kliegr, David Chudán, Andrej Hazucha, Jan Rauch
SEWEBAR-CMS: A System for Postprocessing Data Mining Models. RuleML Challenge (2010)
Tomás Kliegr
Entity classification by bag of Wikipedia articles. PIKM (2010)
Tomás Kliegr, Jan Rauch
An XML Format for Association Rule Models Based on the GUHA Method. RuleML (2010)
Krishna Chandramouli, Tomás Kliegr, Vojtech Svátek, Ebroul Izquierdo
Towards semantic tagging in collaborative environments. DPS (2009)
Tomás Kliegr, Martin Ralbovský, Vojtech Svátek, Milan Simunek, Vojtech Jirkovský, Jan Nemrava, Jan Zemánek
Semantic Analytical Reports: A Framework for Post-processing Data Mining Results. ISMIS (2009)
Jan Nemrava, Tomás Kliegr, Vojtech Svátek, Martin Ralbovský, Jirí Splíchal, Tomás Vejlupek
Semantic annotation and linking of competitive intelligence reports for business clusters. OBI (2008)