Tomás Kliegr

According to our database, Tomás Kliegr authored at least 56 papers between 2008 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

QCBA: improving rule classifiers learned from quantitative data by recovering information lost by discretisation.

Tomás Kliegr, Ebroul Izquierdo

Appl. Intell., September, 2023

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).

Tomás Kliegr, Víctor Gutiérrez-Basulto, Ahmet Soylu

Theory Pract. Log. Program., May, 2023

Apriori Modified for Action Rules Mining.

Lukas Sykora, Tomás Kliegr

Proceedings of the 12th Knowledge Capture Conference 2023, 2023

2022

Why was this cited? Explainable machine learning applied to COVID-19 research literature.

Lucie Beranová, Marcin P. Joachimiak, Tomás Kliegr, Gollam Rabby, Vilém Sklenák

Scientometrics, 2022

Explainability of Text Clustering Visualizations - Twitter Disinformation Case Study.

Jirí Zárský, Gaetan Lopez, Tomás Kliegr

IEEE Computer Graphics and Applications, 2022

High-Utility Action Rules Mining.

Lukas Sykora, Tomás Kliegr, Katerina Hrudková

Proceedings of the 16th International Rule Challenge and 6th Doctoral Consortium @ RuleML+RR 2022 co-located with 18th Reasoning Web Summer School (RW 2022) and 14th DecisionCAMP 2022 as part of Declarative AI 2022, Berlin, Germany (virtual due to Covid-19 pandemic), 26, 2022

2021

RDFRules: Making RDF rule mining easier and even more efficient.

Václav Zeman, Tomás Kliegr, Vojtech Svátek

Semantic Web, 2021

A review of possible effects of cognitive biases on interpretation of rule-based machine learning models.

Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz

Artif. Intell., 2021

2020

On cognitive preferences and the plausibility of rule-based models.

Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim

Mach. Learn., 2020

Editable machine learning models? A rule-based framework for user studies of explainability.

Stanislav Vojír, Tomás Kliegr

Adv. Data Anal. Classif., 2020

Action Rules: Counterfactual Explanations in Python.

Lukas Sykora, Tomás Kliegr

Proceedings of the 14th International Rule Challenge, 4th Doctoral Consortium, and 6th Industry Track @ RuleML+RR 2020 co-located with 16th Reasoning Web Summer School (RW 2020) 12th DecisionCAMP 2020 as part of Declarative AI 2020, Oslo, Norway (virtual due to Covid-19 pandemic), 29 June, 2020

2019

Associative Classification in R: arc, arulesCBA, and rCBA.

Michael Hahsler, Ian Johnson, Tomás Kliegr, Jaroslav Kuchar

R J., 2019

Advances in Machine Learning for the Behavioral Sciences.

Tomás Kliegr, Stepán Bahník, Johannes Fürnkranz

CoRR, 2019

PyIDS - Python Implementation of Interpretable Decision Sets Algorithm by Lakkaraju et al, 2016.

Jirí Filip, Tomás Kliegr

Proceedings of the 13th RuleML+RR 2019 Doctoral Consortium and Rule Challenge, September 16-19, 2019, 2019

Tuning Hyperparameters of Classification Based on Associations (CBA).

Tomás Kliegr, Jaroslav Kuchar

Proceedings of the 19th Conference Information Technologies, 2019

2018

EasyMiner.eu: Web framework for interpretable machine learning based on rules and frequent itemsets.

Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr

Knowl. Based Syst., 2018

Antonyms are similar: Towards paradigmatic association approach to rating similarity in SimLex-999 and WordSim-353.

Tomás Kliegr, Ondrej Zamazal

Data Knowl. Eng., 2018

On Cognitive Preferences and the Interpretability of Rule-based Models.

Johannes Fürnkranz, Tomás Kliegr, Heiko Paulheim

CoRR, 2018

RdfRules Preview: Towards an Analytics Engine for Rule Mining in RDF Knowledge Graphs.

Vaclav Zeman, Tomás Kliegr, Vojtech Svátek

Proceedings of the Doctoral Consortium and Challenge @ RuleML+RR 2018 hosted by 2nd International Joint Conference on Rules and Reasoning (RuleML+RR 2018), 2018

Classification based on Associations (CBA) - A Performance Analysis.

Jirí Filip, Tomás Kliegr

Proceedings of the Doctoral Consortium and Challenge @ RuleML+RR 2018 hosted by 2nd International Joint Conference on Rules and Reasoning (RuleML+RR 2018), 2018

The Need for Interpretability Biases.

Johannes Fürnkranz, Tomás Kliegr

Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

2017

Effect of cognitive biases on human understanding of rule-based machine learning models.

Tomás Kliegr

PhD thesis, 2017

InBeat: JavaScript recommender system supporting sensor input and linked data.

Jaroslav Kuchar, Tomás Kliegr

Knowl. Based Syst., 2017

Quantitative CBA: Small and Comprehensible Association Rule Classification Models.

Tomás Kliegr

CoRR, 2017

Using EasyMiner API for Financial Data Analysis in the OpenBudgets.eu Project.

Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr

Proceedings of the Doctoral Consortium, 2017

Outlier (Anomaly) Detection Modelling in PMML.

Jaroslav Kuchar, Adam Ashenfelter, Tomás Kliegr

Proceedings of the Doctoral Consortium, 2017

EasyMiner - Short History of Research and Current Development.

Tomás Kliegr, Jaroslav Kuchar, Stanislav Vojír, Václav Zeman

Proceedings of the 17th Conference on Information Technologies, 2017

2016

LHD 2.0: A text mining approach to typing entities in knowledge graphs.

Tomás Kliegr, Ondrej Zamazal

J. Web Semant., 2016

Crowdsourced Corpus with Entity Salience Annotations.

Milan Dojchinovski, Dinesh Reddy, Tomás Kliegr, Tomas Vitvar, Harald Sack

Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

2015

Linked hypernyms: Enriching DBpedia with Targeted Hypernym Discovery.

Tomás Kliegr

J. Web Semant., 2015

EasyMiner/R Preview: Towards a Web Interface for Association Rule Learning and Classification in R.

Stanislav Vojír, Vaclav Zeman, Jaroslav Kuchar, Tomás Kliegr

Proceedings of the RuleML 2015 Challenge, 2015

A Brief Overview of Rule Learning.

Johannes Fürnkranz, Tomás Kliegr

Proceedings of the Rule Technologies: Foundations, Tools, and Applications, 2015

Benchmark of Rule-Based Classifiers in the News Recommendation Task.

Tomás Kliegr, Jaroslav Kuchar

Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2015

Multimodal Fusion: Combining Visual and Textual Cues for Concept Detection in Video.

Damianos Galanopoulos, Milan Dojchinovski, Krishna Chandramouli, Tomás Kliegr, Vasileios Mezaris

Proceedings of the Multimedia Data Mining and Analytics - Disruptive Innovation, 2015

2014

Business Rule Learning with Interactive Selection of Association Rules.

Stanislav Vojír, Premysl Václav Duben, Tomás Kliegr

Proceedings of the RuleML 2014 Challenge and the RuleML 2014 Doctoral Consortium hosted by the 8th International Web Rule Symposium, 2014

Learning Business Rules with Association Rule Classifiers.

Tomás Kliegr, Jaroslav Kuchar, Davide Sottara, Stanislav Vojír

Proceedings of the Rules on the Web. From Theory to Applications, 2014

Towards Linked Hypernyms Dataset 2.0: complementing DBpedia with hypernym discovery.

Tomás Kliegr, Ondrej Zamazal

Proceedings of the Ninth International Conference on Language Resources and Evaluation, 2014

Orwellian Eye: Video Recommendation with Microsoft Kinect.

Tomás Kliegr, Jaroslav Kuchar

Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

InBeat: Recommender System as a Service.

Jaroslav Kuchar, Tomás Kliegr

Proceedings of the Working Notes for CLEF 2014 Conference, 2014

2013

Wikipedia Search as Effective Entity Linking Algorithm.

Milan Dojchinovski, Ivo Lasek, Tomás Kliegr, Ondrej Zamazal

Proceedings of the Sixth Text Analysis Conference, 2013

Datasets, GATE Evaluation Framework for Benchmarking Wikipedia-Based NER Systems.

Milan Dojchinovski, Tomás Kliegr

Proceedings of the NLP & DBpedia workshop co-located with the 12th International Semantic Web Conference (ISWC 2013), 2013

Transforming Association Rules to Business Rules: EasyMiner meets Drools.

Stanislav Vojír, Tomás Kliegr, Andrej Hazucha, Radek Skrabal, Milan Simunek

Proceedings of the Joint Proceedings of the 7th International Rule Challenge, 2013

GAIN: web service for user tracking and preference learning - a smart TV use case.

Jaroslav Kuchar, Tomás Kliegr

Proceedings of the Seventh ACM Conference on Recommender Systems, 2013

Entityclassifier.eu: Real-Time Classification of Entities in Text with Wikipedia.

Milan Dojchinovski, Tomás Kliegr

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

KINterestTV - Towards Non-invasive Measure of User Interest While Watching TV.

Julien Leroy, François Rocca, Matei Mancas, Radhwan Ben Madhkour, Fabien Grisard, Tomás Kliegr, Jaroslav Kuchar, Jakub Vit, Ivan Pirner, Petr Zimmermann

Proceedings of the Innovative and Creative Developments in Multimodal Interaction Systems, 2013

2012

Contextualised user profiling in networked media environments.

Dorothea Tsatsou, Lyndon J. B. Nixon, Matei Mancas, Miroslav Vacura, Rüdiger Klein, Julien Leroy, Jaroslav Kuchar, Tomás Kliegr, Manuel Kober, Maria Loli, Vasileios Mezaris

Proceedings of the Workshop and Poster Proceedings of the 20th Conference on User Modeling, 2012

Association Rule Mining Following the Web Search Paradigm.

Radek Skrabal, Milan Simunek, Stanislav Vojír, Andrej Hazucha, Tomás Marek, David Chudán, Tomás Kliegr

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

2011

SEWEBAR-CMS: semantic analytical report authoring for data mining results.

Tomás Kliegr, Vojtech Svátek, Martin Ralbovský, Milan Simunek

J. Intell. Inf. Syst., 2011

Automated matching of data mining dataset schemata to background knowledge.

Stanislav Vojír, Tomás Kliegr, Vojtech Svátek, Ondrej Sváb-Zamazal

Proceedings of the 6th International Workshop on Ontology Matching, 2011

Instant Feedback on Discovered Association Rules with PMML-Based Query-by-Example.

Tomás Kliegr, Andrej Hazucha, Tomás Marek

Proceedings of the Web Reasoning and Rule Systems - 5th International Conference, 2011

2010

An XML Format for Association Rule Models Based on the GUHA Method.

Tomás Kliegr, Jan Rauch

Proceedings of the Semantic Web Rules - International Symposium, 2010

SEWEBAR-CMS: A System for Postprocessing Data Mining Models.

Tomás Kliegr, David Chudán, Andrej Hazucha, Jan Rauch

Proceedings of the RuleML-2010 Challenge, 2010

Entity classification by bag of Wikipedia articles.

Tomás Kliegr

Proceedings of the Third Ph.D. Workshop on Information and Knowledge Management, 2010

2009

Semantic Analytical Reports: A Framework for Post-processing Data Mining Results.

Tomás Kliegr, Martin Ralbovský, Vojtech Svátek, Milan Simunek, Vojtech Jirkovský, Jan Nemrava, Jan Zemánek

Proceedings of the Foundations of Intelligent Systems, 18th International Symposium, 2009

Towards semantic tagging in collaborative environments.

Krishna Chandramouli, Tomás Kliegr, Vojtech Svátek, Ebroul Izquierdo

Proceedings of the 16th International Conference on Digital Signal Processing, 2009

2008

Semantic annotation and linking of competitive intelligence reports for business clusters.

Jan Nemrava, Tomás Kliegr, Vojtech Svátek, Martin Ralbovský, Jirí Splíchal, Tomás Vejlupek

Proceedings of the First International Workshop on Ontology-supported Business Intelligence, 2008