Reductiontechniques for Instance Based Text Categorization. - Peter Bednár; Tomáss Futej (BASYS, 2004)

A comparison of the bagging and the boosting methods using the decision trees classifiers. - Kristína Machova; Miroslav Puszta; Frantisek Barcák; Peter Bednár (Comput. Sci. Inf. Syst., 2006)

Various Approaches to Web Information Processing. - Kristína Machova; Peter Bednár; Marian Mach (Comput. Informatics, 2007)

Semantic Integration of eGovernment Services in Schleswig-Holstein. - Peter Bednár; Karol Furdík; Maren Kleimann; Ralf Klischewski; Marek Skokan; Stefan Ukena (EGOV, 2008)

Use of Semantic Principles in a Collaborative System in Order to Support Effective Information Retrieval. - Frantisek Babic; Karol Furdík; Ján Paralic; Peter Bednár; Jozef Wagner (ICCCI, 2009)

Access-EGov - A Real World Semantic Service-oriented Architecture for E-Government. - Rolf Schillinger; Stefan Durbeck; Peter Bednár (Wirtschaftsinformatik (2), 2009)

Prediction of significant meteorological phenomena using advanced data mining and integration methods. - Ladislav Hluchý; Ondrej Habala; Juraj Bartok; Peter Bednár; Martin Gazák (FSKD, 2010)

Analytical Framework for Mirroring and Reflection of User Activities in E-Learning Environment. - Frantisek Babic; Ján Paralic; Peter Bednár; Michal Racek (MISSI, 2010)

KP-Lab System for the Support of Collaborative Learning and Working Practices, Based on Trialogical Learning. - Ján Paralic; Frantisek Babic; Jozef Wagner; Peter Bednár; Marek Paralic (Informatica (Slovenia), 2010)

Data mining and integration for predicting significant meteorological phenomena. - Juraj Bartok; Ondrej Habala; Peter Bednár; Martin Gazák; Ladislav Hluchý (ICCS, 2010)

DS3I - A Dynamic Semantically Enhanced Service Selection Infrastructure. - Christoph Fritsch; Peter Bednár; Günther Pernul (EC-Web, 2011)

Meteorological Phenomena Forecast Using Data Mining Prediction Methods. - Frantisek Babic; Peter Bednár; Frantisek Albert; Ján Paralic; Juraj Bartok; Ladislav Hluchý (ICCCI (1), 2011)

Integration of Government Services using Semantic Technologies. - Ján Hreno; Peter Bednár; Karol Furdík; Tomas Sabol (J. Theor. Appl. Electron. Commer. Res., 2011)

Support of Semantic Interoperability in a Service-based Business Collaboration Platform. - Karol Furdík; Peter Bednár; Gabriel Lukac; Christoph Fritsch (Scalable Comput. Pract. Exp., 2011)

Design and integration of ICT tools for OCOPOMO policy modelling approach. - Peter Bednár; Peter Butka; Karol Furdík; Marian Mach; Peter Smatana (SACI, 2012)

Romancing the Stone - Aiding Sense-Making in Organizations. - Peter Bednár; Gill Green (UKAIS, 2012)

Integrated OCOPOMO toolset for open collaboration in policy modelling. - Peter Bednár; Peter Smatana (SACI, 2013)

Personalized and Adaptive Access to Services - The Semantic Web Services Approach. - Marek Paralic; Peter Bednár; Ján Paralic (Semantic Hyper/Multimedia Adaptation, 2013)

Analytical Platform Based on Jbowl Library Providing Text-Mining Services in Distributed Environment. - Martin Sarnovsky; Peter Butka; Peter Bednár; Frantisek Babic; Ján Paralic (ICT-EurAsia/CONFENIS, 2015)

Cross-Language Dependency Parsing Using Part-of-Speech Patterns. - Peter Bednár (TSD, 2016)

Conceptualization of social big data: Keynote. - Peter Bednár (SMAP, 2017)

Big Data Processing and Analytics Platform Architecture for Process Industry Factories. - Martin Sarnovsky; Peter Bednár; Miroslav Smatana (Big Data Cogn. Comput., 2018)

Semantic Models for Network Intrusion Detection. - Peter Bednár; Martin Sarnovsky; Pavol Halas (SAM IoT, 2020)

Unmasking the drivers and Implementation of change. - Fatema Zaghloul; Peter Bednár (STPIS, 2021)

Semantic automatization of the data-analytical processes. - Peter Bednár; Juliana Ivancáková; Martin Sarnovsky (SACI, 2022)

New Ways of Exploring Connections Between Cultural Heritage Objects. - Peter Smatana; Tomas Sabol; Ján Hreno; Peter Bednár; Michaela Smatanova (SACI, 2022)

Cognitive Architecture for Process industries. - Peter Bednár; Martin Sarnovsky; Jakub Ivan Vanko (eSAAM, 2023)

Unraveling COVID-19 Dynamics via Machine Learning and XAI: Investigating Variant Influence and Prognostic Classification. - Oliver Lohaj; Ján Paralic; Peter Bednár; Zuzana Paralicová; Matús Huba (Mach. Learn. Knowl. Extr., 2023)

Leveraging Structural Causal Models for Bias Detection and Feature Adjustment in Machine Learning Predictions. - Bern Igoche Igoche; Olumuyiwa Matthew; Peter Bednár; Alexander E. Gegov (IS, 2024)