Research

Publications

Book, Book chapter

  1. Márta Alexy, Tomaš Horváth: Tracing the local breeds in an outdoor system - a Hungarian example with Mangalica pig breed. Chapter 5, Tracing the Domestic Pig (edited by Dr. Goran Kušec), IntechOpen, London.
  2. J. Moreira, A. C.P.L.F. de Carvalho, T Horváth: A General Introduction to Data Analytics. Wiley, ISBN: 978-1-119-29626-3, 2018, 352 pages.
  3. N. Thai-Nghe, L. Drumond, T. Horváth, A. Krohn-Grimberghe, A. Nanopoulos, L. Schmidt-Thieme: Factorization Techniques for Predicting Student Performance. In Educational Recommender Systems and Technologies: Practices and Challenges, Olga C. Santos and Jesus G. Boticario (eds.), IGI Global, ISBN: 978-1-613-50489-5, 2011, pp: 129-153.

Proceedings

  1. M. Holeňa, T. Horváth, A. Kelemenová, F. Mráz, D. Pardubská, M. Plátek, P. Sosík: Proceedings of the 20th Conference Information Technologies - Applications and Theory (ITAT 2020). Hotel Tyrapol, Oravská Lesná, Slovakia, September 18-22, 2020, Published in CEUR Workshop Proceedings vol. 2718, ISSN 1613-0073.
  2. P. Barančíková, M. Holeňa, T. Horváth, M. Pleva, R. Rosa: Proceedings of the 19th Conference Information Technologies - Applications and Theory (ITAT 2019). Hotel Zornička, Donovaly, Slovakia, September 20-24, 2019, Published in CEUR Workshop Proceedings vol. 2473, ISSN 1613-0073.
  3. A. Benczúr, B. Thalheim, T. Horváth, S. Chiusano, T. Cerquitelli, C. Sidló, P. Z. Revesz: Proceedings of Short Papers and Workshops of the 22nd European Conference ADBIS 2018. Budapest, Hungary, September 2-5, 2018, Published in New Trends in Databases and Information Systems, CCIS, volume 909, Springer, ISSN 1865-0929, ISBN 978-3-030-00062-2.
  4. A. Benczúr, B. Thalheim, T. Horváth: Proceedings of the 22nd European Conference ADBIS 2018. Budapest, Hungary, September 2-5, 2018, Published in Advances in Databases and Information Systems, LNCS, volume 11019, Springer, ISSN 0302-9743, ISBN 978-3-319-98397-4.
  5. M. Kravčík, O. C. Santos, J. G. Boticario, M. Bieliková, T. Horváth, I. Torre: Proceedings of the 8th International Workshop on Personalization Approaches in Learning Environments PALE 2018. London, UK, June 30th, 2018, Published in CEUR Worskhop Proceedings vol. 2141, ISSN 1613-0073.
  6. M. Kravčík, O. C. Santos, J. G. Boticario, M. Bieliková, T. Horváth: Proceedings of the 5th International Workshop on Personalization Approaches in Learning Environments PALE 2015. Dublin, Ireland, June 30th, 2015, Published in CEUR Workshop Proceedings vol. 1388, ISSN 1613-0073.
  7. J. Pokorný, P. Šaloun, J. Paralič, T. Horváth: Proceedings of joint Conferences Znalosti and Datakon 2013. VŠB-Technical University Ostrava, Czech Republic, October 13-15, 2013, ISBN 978-80-248-3189-3, pp. 360.
  8. T. Horváth: Proceedings of the Conference on Theory and Practice of Information Technologies, ITAT 2012. Hotel Magura, Slovakia, September 17-21, 2012, ISBN 978-80-971144-0-4, pp. 69. (available also in CEUR)
  9. T. Horváth: Zborník príspevkov prezentovaných na konferencii Informačné technológie – Aplikácie a Teória, ITAT 2012. Hotel Magura, 17-21. septembra 2012, ISBN 978-80-971144-1-1, pp. 73.
  10. P. Bednár, T. Horváth, J. Paralič, A. Rauber: Proceedings of the 6th Workshop on Data Analysis (WDA 2005): Elfa Academic Press, ISBN: 80-8086-015-7, 2005, Kosice, pp. 99.

Journal articles

  1. Z. Farou, Y. Wang, T. Horváth: Cluster-Based Oversampling with Area Extraction from Representative Points for Class Imbalance Learning. Accepted to INTELLIGENT SYSTEMS WITH APPLICATIONS, Volume 22, 200357, Elsevier, 2024, ISSN 2667-3053.
  2. R. G. Mantovani, T. Horváth, A. L. D. Rossi, R. Cerri, S. Barbon Junior, J. Vanschoren, A. C. P. L. F. de Carvalho: Better Trees: An empirical study on hyperparameter tuning of classification decision tree induction algorithms. DATA MINING AND KNOWLEDGE DISCOVERY, Springer, 2024, ISSN 1384-5810.
  3. T. Misikir Tashu, M. Lenz, T. Horváth: NCC: Neural Concept Compression for Multilingual Document Recommendation. APPLIED SOFT COMPUTING, Vol. 142, 110348, Elsevier, 2023, ISSN 1568-4946.
  4. T. Horváth, R. G. Mantovani, A. C. P. L. F. de Carvalho: Hyper-parameter Initialization of Classification Algorithms using Dynamic Time Warping: A Perspective on PCA Meta-features. APPLIED SOFT COMPUTING, Vol. 134, 109969, Elsevier, 2023, ISSN 1568-4946.
  5. D.T. Várkonyi, J.L. Seixas Junior, T. Horváth: Dynamic Noise Filtering for Multi-class Classification of Beehive Audio Data. EXPERT SYSTEMS WITH APPLICATIONS, Vol. 213, Part A, 2023, Elsevier, ISSN 0957-4174.
  6. D. Horváth, G. Erdős, Z. Istenes, T. Horváth, S. Földi: Object Detection Using Sim2Real Domain Randomization for Robotic Applications. IEEE TRANSACTION ON ROBOTICS, Vol. 39, No. 2, IEEE Press, 2023, ISSN 1552-3098, p: 1225-1243.
  7. T. Misikir Tashu, S. Hajiyeva, T. Horváth: Multimodal Emotion Recognition from Art Using Sequential Co-Attention. JOURNAL OF IMAGING, Volume 7, No. 8:157, MDPI, 2021, ISSN 2313-433X, p: 1-12.
  8. L. Peška, T. Misikir Tashu, T. Horváth: Swarm Intelligence Techniques in Recommender Systems - A Review of Recent Research. SWARM AND EVOLUTIONARY COMPUTATION, Volume 48, Elsevier, 2019, ISSN 2210-6502, p: 201-219.
  9. T. Horváth, A. C. P. L. F. de Carvalho: Evolutionary Computing in Recommender Systems: A Review of Recent Research. NATURAL COMPUTING, Volume 16, Issue 3, Springer Verlag, 2017, ISSN 1567-7818, p: 441-462.
  10. L. Pisková, T. Horváth, S. Krajči: Ranking Formal Concepts by Utilizing Matrix Factorization. STUDIA UNIV. BABES–BOLYAI, INFORMATICA, Volume LIX, Special Issue 2, 2014 (12th International Conference on Formal Concept Analysis, Cluj-Napoca, 2014), Babes-Bolyai University, ISSN 1224-869x, p: 62-79.
  11. R. Janning, A. Busche, T. Horváth, L. Schmidt-Thieme: Buried Pipe Localization Using an Iterative Geometric Clustering on GPR Data. ARTIFICIAL INTELLIGENCE REVIEW, Volume 42, Issue 3, Springer Verlag, 2013, ISSN 0269-2821, 2013, p. 403-425.
  12. K. Buza, A. Nanopoulos, T. Horváth, L. Schmidt-Thieme: GRAMOFON: General Model-selection Framework based on Networks. NEUROCOMPUTING 75 (2012): Elsevier, 2012, ISSN 0925-2312, pp: 163-170.
  13. T. Horváth: A Model of User Preference Learning for Content-Based Recommender Systems. COMPUTING AND INFORMATICS Vol. 28 (2009), No. 4: SAV, Slovakia, 2009, ISSN 1335-9150, pp: 453-481.
  14. P. Gurský, T. Horváth, J. Jirásek, S. Krajči, R. Novotný, J. Pribolová, V. Vaneková, P. Vojtáš: User Preference Web Search - Experiments with a System Connecting Web and User. COMPUTING AND INFORMATICS Vol. 28 (2009), No. 4: SAV, Slovakia, 2009, ISSN 1335-9150, pp: 515-553.
  15. P. Gurský, T. Horváth, J. Jirásek, R. Novotný, J. Pribolová, V. Vaneková, P. Vojtáš: Knowledge Processing for Web Search – An Integrated Model and Experiments. SCALABLE COMPUTING: PRACTICE AND EXPERIENCE Volume 9, Number 1 (2008): SWPS, Poland, 2008, ISSN 1895-1767, p:51–59.
  16. T. Horváth, S. Krajči: Integration of two fuzzy data mining methods. NEURAL NETWORK WORLD Volume 14 (2004): AV ČR, Czech Republic, 2004, ISSN 1210-0552, p:391-402.
  17. T. Horváth, S. Krajči, R. Lencses, P. Vojtáš: An ILP model for a graded classification problem. KYBERNETIKA Volume 40, Number 3 (2004): AV ČR, Czech Republic, 2004, ISSN 0023-5954, p:317–332.

Conference papers

  1. Z. Farou, M. Aharrat T. Horváth: A Comparative Study of Assessment Metrics for Imbalanced Learning. Short Papers, Doctoral Consortium and Workshops Proceedings of the 27th International Conference on Advances in Databases and Information Systems (ADBIS), 2023 Barcelona, Spain: Communications in Computer and Information Science, Vol. 1850, Springer, Cham, p: 119–129.
  2. Ľ. Antoni, P. Eliaš, T. Horváth, S. Krajči, O. Krídlo, C. Török: Squared symmetric formal contexts and their connections with correlation matrices. Accepted to the 28th International Conference on Conceptual Structures (ICCS), Berlin, Germany, 2023.
  3. T. Misikir Tashu, S. Fattouh, P. Kiss, T. Horváth: Multimodal E-Commerce Product Classification Using Hierarchical Fusion. Proceedings of the 2nd IEEE Conference on Information Technology and Data Science (CITDS) 2022, Debrecen, Hungary: IEEE, p: 279-284.
  4. S. Ouaari, T. Misikir Tashu, T. Horváth: Multimodal Feature Extraction for Memes Sentiment Classification. Proceedings of the 2nd IEEE Conference on Information Technology and Data Science (CITDS) 2022, Debrecen, Hungary: IEEE, p: 285-290.
  5. T. Misikir Tashu, T. Horváth: Synonym-Based Essay Generation and Augmentation for Robust Automatic Essay Scoring. 23rd International Conference on Intelligent Data Engineering and Automated Learning, 2022. IDEAL 2022, Manchester, UK: Lecture Notes in Computer Science, Vol. 13756, Springer, Cham, p: 12-21.
  6. Z. Farou, L. Kopeikina, T. Horváth: Solving Multi-class Imbalance Problems Using Improved Tabular GANs. 23rd International Conference on Intelligent Data Engineering and Automated Learning, 2022. IDEAL 2022, Manchester, UK: Lecture Notes in Computer Science, Vol. 13756, Springer, Cham, p: 527-539.
  7. W. Skaf, T. Horváth: Denoising Architecture for Unsupervised Anomaly Detection in Time-Series. Proceedings of Short papers, Workshops, and Doctoral Consortium of ADBIS 2022: New Trends in Database and Information Systems, Torino, Italy: Communications in Computer and Information Science, Vol. 1652. Springer, Cham, p: 178-187.
  8. E. Birihanu, J. Mahmud, P. Kiss, A. Kamuzora, W. Skaf, T. Horváth, T. Jursonovics, P. Pogrzeba, I. Lendák: Client Error Clustering Approaches in Content Delivery Networks (CDN). Proceedings of the 22nd Industrial Conference on Data Mining 2022, New York, USA: ibai-publishing, p: 51-63.
  9. Z. Farou, S. Ouaari, B. Domian, T. Horváth: Directed Undersampling Using Active Learning for Particle Identification. Proceedings of the 4th International Conference on Recent Innovations in Computing 2021, Budapest, Hungary: Lecture Notes in Electrical Engineering, Vol. 855, Springer, p: 149-162.
  10. T. Horváth, R. G. Mantovani, A. C. P. L. F. de Carvalho: Time-Series in Hyper-parameter Initialization of Machine Learning Techniques. Proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning 2021, Manchester, UK: Lecture Notes in Computer Science, Vol. 13113, Springer, p: 246–258.
  11. M. Lenz, T. Misikir Tashu, T. Horváth: Learning Inter-Lingual Document Representations via Concept Compression. Proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning 2021, Manchester, UK: Lecture Notes in Computer Science, Vol. 13113, Springer, p: 268–276.
  12. V. T. Salamon, T. Misikir Tashu, T. Horváth: Linear Concept Approximation for Multilingual Document Recommendation. Proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning 2021, Manchester, UK: Lecture Notes in Computer Science, Vol. 13113, Springer, p: 147–156.
  13. A. Galloni, I. Lendák, T. Horváth: A Novel Evaluation Metric for Synthetic Data Generation. Proceedings of the 21st International Conference on Intelligent Data Engineering and Automated Learning 2020 - Part II, Guimaraes, Portugal: Lecture Notes in Computer Science, Vol. 12490, Springer, p: 25-34.
  14. Z. Farou, N. Mouhoub, T. Horváth: Data Generation Using Gene Expression Generator. Proceedings of the 21st International Conference on Intelligent Data Engineering and Automated Learning 2020 - Part II, Guimaraes, Portugal: Lecture Notes in Computer Science, Vol. 12490, Springer, p: 54-65.
  15. P. Kiss, T. Horváth, V. Felbab: Stateful Optimization in Federated Learning of Neural Networks. Proceedings of the 21st International Conference on Intelligent Data Engineering and Automated Learning 2020 - Part II, Guimaraes, Portugal: Lecture Notes in Computer Science, Vol. 12490, Springer, p: 348-355.
  16. T. Misikir Tashu, T. Horváth: SmartScore-Short Answer Scoring Made Easy Using Sem-LSH. Proceedings of the IEEE 14th International Conference on Semantic Computing 2020, San Diego, California, US: IEEE, p: 145-149.
  17. M. Alexy, T. Horváth, C. Reich, J. Felföldi, A. Tarcsi: Adaption of data-intensive monitoring and tracking systems in outdoor pig production for better decision making - literature review and project idea. Proceedings of the 9th European Conference on Precision Livestock Farming 2019, Cork, Ireland, ISBN 978-1-84170-654-2, p. 684-691.
  18. K. Buza, T. Horváth: Factorization Machines for Blog Feedback Prediction. Proceedings of the 11th International Conference on Computer Recognition Systems 2019, Polanica-Zdroj, Poland: Advances in Intelligent Systems and Computing, Vol. 977, Springer, p: 79-85.
  19. T. Misikir Tashu, T. Horváth: A Layered Approach to Automatic Essay Evaluation Using Word-Embedding. Selected papers of the 15th International Conference on Computer Supported Education 2018, Madeira, Portugal: Communications in Computer and Information Science, Vol. 1022, Springer, p: 77-94.
  20. T. Misikir Tashu, T. Horváth, J. P. Esclamado: Intelligent On-line Exam Management and Evaluation System. Proceedings of the 15th International Conference on Intelligent Tutoring Systems 2019, Jamaica: Lecture Notes in Computer Science, Vol. 11528, Springer, p: 105-111.
  21. T. Misikir Tashu, T. Horváth, D. Szabó: Reducing Annotation Effort in Automatic Essay Evaluation Using Locality Sensitive Hashing. Proceedings of the 15th International Conference on Intelligent Tutoring Systems 2019, Jamaica: Lecture Notes in Computer Science, Vol. 11528, Springer, p: 186-192.
  22. T. Misikir Tashu, T. Horváth: Semantic-Based Feedback Recommendation for Automatic Essay Evaluation. SAI Intelligent Systems Conference (Advances in Intelligent Systems and Computing; 1038), Springer International Publishing 2019, ISBN:978-3-030-29512-7, p. 334-346.
  23. P. Kiss, D. Fonyó, T. Horváth: BlaBoO: A Lightweight Black Box Optimizer Framework. World Symposium on Digital Intelligence for Systems and Machines 2018, Košice, Slovakia: IEEE, p. 213-218.
  24. T. Misikir Tashu, T. Horváth: Pair-Wise: Automatic Essay Evaluation using Word Mover’s Distance. Proceedings of the 11th International Conference on Computer Supported Education (CSEDU '18): SCITEPRESS, 2018. ISBN: 978-989-758-291-2, p. 59-66.
  25. T. Horváth, R. G. Mantovani, A. C. P. L. F. de Carvalho: Effects of Random Sampling on SVM Hyper-parameter Tuning. Intelligent Systems Design and Applications (Advances in Intelligent Systems and Computing; 557.), Springer International Publishing 2017, ISBN:978-3-319-53479-4, p. 268-278.
  26. R. G. Mantovani, T. Horváth, R. Cerri, A. C. P. L. F. de Carvalho, J. Vanschoren: Hyper-parameter Tuning of a Decision Tree Induction Algorithm. 5th Brazilian Conference on Intelligent Systems (BRACIS): IEEE, 2016, p. 37-42.
  27. Š. Pero, T. Horváth: Comparison of Collaborative-filtering Techniques for Small-scale Student Performance Prediction Task. In Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering: Lecture Notes in Electrical Engineering (vol. 313), Springer, 2015, ISSN 1876-1100, ISBN 978-3-319-06772-8, p. 111-116.
  28. Š. Pero, T. Horváth: A Web-based Intelligent Tutoring System for Introductory Programming. In Type II Proceedings of the WIC 2014 Web Intelligence Congress (WI '14), Warsaw, 2014, p. 20-21.
  29. Š. Pero, T. Horváth: How patterns in source codes of students can help in detection of their programming skills? In Proceedings of the 7th International Conference on Educational Data Mining (EDM '14), London, England, 2014, ISBN 978-0-9839525-4-1, 2014, p. 371-372.
  30. L. Pisková, T. Horváth: Computing Concept Lattices from Very Sparse Large-Scale Formal Contexts. In Proceedings of the 21st International Conference on Conceptual Structures, (ICCS), LECTURE NOTES IN COMPUTER SCIENCE (vol. 8577), Springer, 2014, ISSN 0302-9743, ISBN 978-3-642-38843-9, p. 245-259.
  31. A. Busche, R. Janning, T. Horváth, L. Schmidt-Thieme: A Unifying Framework for GPR Image Reconstruction. In Data Analysis, Machine Learning and Knowledge Discovery (Part VI): Springer, Studies in Classification, Data Analysis, and Knowledge Organization, 2014, ISBN 978-3-319-01594-1, ISSN 1431-8814, p. 325-332.
  32. L. Piskova,T. Horváth: Comparing Performance of Formal Concept Analysis and Closed Frequent Itemset Mining Algorithms on Real Data. Proceedings of the 10th International Conference on Concept Lattices and Their Applications: Laboratory L3i, University of La Rochelle, France, 2013, ISBN 978–2–7466–6566–8, p. 299-304.
  33. Š. Pero, T. Horváth. Opinion-Driven Matrix Factorization for Rating Prediction. In 21st International Conference on User Modeling, Adaptation, and Personalization (UMAP '13), Rome, Italy, 2013: LECTURE NOTES IN COMPUTER SCIENCE (vol. 7899), Springer, 2013, ISSN 0302-9743, ISBN 978-3-642-38843-9, p. 1-13.
  34. Š. Pero, T. Horváth. Detection of Inconsistencies in Student Evaluations. The 5th International Conference on Computer Supported Education (CSEDU '13), Aachen, Germany, 2013: ScitePress, 2013, p. 246-249.
  35. L. Piskova, Š. Pero, T. Horváth, S. Krajči: Mining Concepts from Incomplete Datasets Utilizing Matrix Factorization. Proceedings of the 9th International Conference on Concept Lattices and Their Applications: Universidad de Málaga, Spain, 2012, ISBN 9788469552520, p. 33-44.
  36. R. Janning, T. Horváth, A. Busche, L. Schmidt-Thieme: Pipe Localization by Apex Detection. International Conference on Radar Systems, Glasgow, UK, 2012: The Institution of Engineering and Technology IET, ISBN 978-1-84919-676-5, 2012.
  37. R. Janning, T. Horváth, A. Busche, L. Schmidt-Thieme: GamRec: a Clustering Method Using Geometrical Background Knowledge for GPR Data Preprocessing. Proceedings of to the 8th International Conference on Artificial Intelligence Applications and Innovations, Halkidiki, Greece: Springer, IFIP Advances in Information and Communication Technology Volume 381, ISBN 978-3-642-33409-2, 2012, p: 347-356.
  38. T. Horváth, A. Eckhardt, K. Buza, P. Vojtáš, L. Schmidt-Thieme: Value-transformation for Monotone Prediction by Approximating Fuzzy Membership Functions. In the 12th IEEE International Symposium on Computational Intelligence and Informatics, Budapest, Hungary, 2011: IEEE, ISBN 978-1-4577-0044-6, 2011, pp: 367-372.
  39. N. Thai-Nghe, T. Horváth, L. Schmidt-Thieme: Personalized Forecasting Student Performance. The 11th IEEE International Conference on Advanced Learning Technologies (ICALT '11), Athens, Georgia, USA, 2011: IEEE Computer Society, 2011, ISBN 978-0-7695-4346-8, p: 412-414.
  40. N. Thai-Nghe, T. Horváth, L. Schmidt-Thieme: Factorization Models for Forecasting Student Performance. In 4th International Conference on Educational Data Mining (EDM'11), Eindhoven, The Netherllands, 2011: TU/e printservice, Eindhoven, ISBN 978-90-386-2537-9, p: 11-20.
  41. N. Thai-Nghe, L. Drumond, T. Horváth, A. Nanopoulos, L. Schmidt-Thieme: Matrix and Tensor Factorization for Predicting Student Performance. In Proceedings of the 3rd Internaitonal Conference on Computer Supported Education (CSEDU '11), Noordwijkerhout, The Netherlands, 2011, Volume 1: SciTePress, Portugal, 2011, ISBN 78-989-8425-49-2, p: 69-78.
  42. A. Eckhardt, T. Horváth, D. Maruščák, R. Novotný, P. Vojtáš: Uncertainty Issues and Algorithms in Automating Process Connecting Web and User. In: Uncertainty Reasoning for the Semantic Web I, ISWC International Workshops, URSW 2005-2007, Revised Selected and Invited Papers: LECTURE NOTES IN COMPUTER SCIENCE (vol. 5327), Springer-Verlag Berlin Heidelberg, 2008, ISSN 0302-9743, ISBN 978-3-540-89764-4, pp: 207-223.
  43. P. Gurský, T. Horváth, J. Jirásek , S. Krajči, R. Novotný, V. Vaneková, P. Vojtáš: Knowledge Processing for Web Search – An Integrated Model. In: C. Badica and M. Paprzycki (eds.) Proceedings of the 1st International Symposium on Intelligent and Distributed Computing (IDC 2007), Craiova, Romania, 2007: STUDIES IN COMPUTATIONAL INTELLIGENCE (vol. 78), Springer, 2007, ISSN 1860-949X, ISBN 978-3-540-74929-5, pp: 95-104.
  44. A. Eckhardt, T. Horváth, P. Vojtáš: PHASES: A User Profile Learning Approach for Web Search. Proceedings of the 2007 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2007), Silicon Valley, USA : IEEE Computer Society, 2007, ISBN 0-7695-3026-5, pp: 780-783.
  45. A. Eckhardt, T. Horváth, P. Vojtáš: Learning Different User Profile Annotated Rules for Fuzzy Preference Top-k Querying. In: W. Liu, V.S. Subrahmanian, H. Prade, T. Lukasiewicz (Eds.): Proceedings of the 1th International Conference on Scalable Uncertainty Management, (SUM '07), Washington DC, USA, 2007: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE (vol. 4772), Springer-Verlag Berlin Heidelberg, 2007, ISSN 0302-9743, ISBN 978-3-540-75407-7, pp: 116-130, 2007.
  46. T. Horváth, P. Vojtáš: Induction of Fuzzy and Annotated Logic Programs. In: S. Muggleton, R. Otero, and A. Tamaddoni-Nezhad (Eds.): Main (Post Conference -) Proceedings of the the 16th International Conference on Inductive Logic Programming (ILP '06),Santiago de Compostela, Spain, 2006: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE (vol. 4455), Springer-Verlag Berlin Heidelberg, 2007, ISSN 0302-9743, ISBN 978-3-540-73846-6, pp. 260–274.
  47. P. Gursky, T. Horvath, J. Jirasek, S. Krajci, R. Novotny, V. Vanekova, P. Vojtas: Web Search with Variable User Model. In: Proceedings of Conference DATAKON '07, Brno, Czech Republic, 2007: Masaryk University, Czech Republic, 2007, ISBN 978-80-7355-076-9, p: 111-121.
  48. P. Gurský, T. Horváth, R. Novotný, V. Vaneková, P. Vojtáš: UPRE: User preference based search system. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI '06), Hong Kong, 2006: IEEE Computer Society, 2006, ISBN 0-7695-2747-7, p: 841-844.
  49. T. Horváth, P. Vojtáš: Ordinal Classification with Monotonicity Constraints. In. P. Perner (ed.) Proceedings of the 6th Industrial Conference on Data Mining (ICDM '06), Leipzig, Germany, 2006: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE (vol. 4065), Springer, 2006, ISSN 0302-9743, ISBN 3-540-36036-0, p: 217-225.
  50. T. Horváth, P. Vojtáš: Fuzzy induction via generalized annotated programs. In: 8th International Conference on Computational Intelligence (Fuzzy Days, Dortmund '04), Dortmund, Germany, 2004: Springer, ADVANCES IN SOFT COMPUTING SERIES (tit. Computational Intelligence, Theory and Applications), 2005, ISSN 1615-3871, ISBN 3-540-22807-1, p:419-433.
  51. P. Gurský, T. Horváth: Dynamic search of relevant information. In: 4th Conference ZNALOSTI '05, Stará Lesná, Slovakia, 2005: FEI VŠB-TU Ostrava, Czech Republic, 2005, ISBN 80-248-0755-6, p:194-201.
  52. T. Horváth, F. Sudzina, P. Vojtáš: Mining rules from monotone classification measuring impact of information systems on business competitiveness. In: 6th IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing and Services (BASYS '04), Wien, Austria, 2004: Springer, IFIP International Federation for Information Processing (vol. 159) 2005, ISSN 1571-5736, ISBN 0-387-22828-4, p:451-458.
  53. T. Horváth, S. Krajči: Integration of methods of Clustering via Conceptual lattices and Inductive logic programming for a graded classification problem. In: 3rd Conference ZNALOSTI '04, Brno, Czech Republic, 2004: FEI VŠB-TU Ostrava, Czech Republic, 2004, ISBN 80-248-0456-5, p:297–308.

Workshop papers

  1. D.T. Várkonyi, M. Alexy, T. Horváth: Beyond Sensor Data Analysis: Unexpected Challenges in a Honeybee Monitoring Project. ITAT 2022 Information Technologies - Applications and Theory, Zuberec, Slovakia, 2022: CEUR Workshop Proceedings Vol-3226, ISSN 1613-0073, 2022, p: 61-67.
  2. T. Misikir Tashu, T. Horváth: Attention-based Multi-modal Emotion Recognition From Art. International Workshop on Fine Art Pattern Extraction and Recognition (FAPER 2020) in conjunction with the 25th International Conference on Pattern Recognition (ICPR 2020), Milano, Italy (virtual): Lecture Notes in Computer Science, Vol. 12663. Springer, Cham, 2021, p: 604-612.
  3. P. Kiss, T. Horváth: Migrating models: A decentralized view on federated learning. International Workshops of the International Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Bilbao, Spain (virtual): Communications in Computer and Information Science, vol 1524. Springer, Cham, 2021, p: 177-191.
  4. E. Zolotareva, T. Misikir Tashu, T. Horváth: Abstractive Text Summarization using Transfer Learning. ITAT 2020 Information Technologies - Applications and Theory, Hotel Tyrapol, Oravská Lesná, Slovakia, 2020: CEUR Workshop Proceedings Vol-2718, ISSN 1613-0073, 2020, p: 75-80.
  5. A. Balawi, A. Al Zoabi, J.L. Seixas Junior, T. Horváth: Classification of a Small Imbalanced Dataset of Vine Leaves Images using Deep Learning Techniques. ITAT 2020 Information Technologies - Applications and Theory, Hotel Tyrapol, Oravská Lesná, Slovakia, 2020: CEUR Workshop Proceedings Vol-2718, ISSN 1613-0073, 2020, p: 108-114.
  6. J.L. Seixas Junior, T. Horváth: KNN Algorithm with DTW Distance for Signature Classification of Wine Leaves. ITAT 2020 Information Technologies - Applications and Theory, Hotel Tyrapol, Oravská Lesná, Slovakia, 2020: CEUR Workshop Proceedings Vol-2718, ISSN 1613-0073, 2020, p: 130-136.
  7. G. Szegedi, D. Bajdikné Veres, I. Lendák, T. Horváth: Context-based Information Classification on Hungarian Invoices. ITAT 2020 Information Technologies - Applications and Theory, Hotel Tyrapol, Oravská Lesná, Slovakia, 2020: CEUR Workshop Proceedings Vol-2718, ISSN 1613-0073, 2020, p: 147-151.
  8. R.K. Szabó, T. Horváth, Á. Tarcsi: Analysis of Delay Patterns and Correlations in Railway Traffic Data. ITAT 2020 Information Technologies - Applications and Theory, Hotel Tyrapol, Oravská Lesná, Slovakia, 2020: CEUR Workshop Proceedings Vol-2718, ISSN 1613-0073, 2020, p: 152-160.
  9. C.K. Maurya, N. Gantayat, S, Dechu, and T. Horváth: "Online Similarity Learning with Feedback for Invoice Line Item Matching." Proceedings of the AAAI-20 Workshop on Intelligent Process Automation (IPA-20), New York, US: arXiv:2001.00288, 2020, p. 1-8.
  10. G. Szegedi, P. Kiss, T. Horváth: Evolutionary Federated Learning on EEG-data. ITAT 2019 Information Technologies - Applications and Theory, Hotel Zornička, Donovaly, Slovakia, 2019: CEUR Workshop Proceedings Vol-2473, ISSN 1613-0073, 2019, p: 71-78.
  11. V. Felbab, P. Kiss, T. Horváth: Optimization in Federated Learning. ITAT 2019 Information Technologies - Applications and Theory, Hotel Zornička, Donovaly, Slovakia, 2019: CEUR Workshop Proceedings Vol-2473, ISSN 1613-0073, 2019, p: 58-65.
  12. I. Lendák, T. Horváth: Efficient Load Profiling and Forecasting in Large Electric Power Systems. ITAT 2019 Information Technologies - Applications and Theory, Hotel Zornička, Donovaly, Slovakia, 2019: CEUR Workshop Proceedings Vol-2473, ISSN 1613-0073, 2019, p: 36-43.
  13. Andrea Galloni, Balázs Horváth, Tomáš Horváth: Real-time Monitoring of Hungarian Highway Traffic from Cell Phone Network Data. ITAT 2018 Information Technologies - Applications and Theory, Hotel Plejsy, Slovakia, 2018: CEUR Workshop Proceedings Vol-2203, ISSN 1613-0073, 2018, p: 108-115.
  14. Balázs Horváth, Tomáš Horváth: Evaluating Data Sources for Crawling Events from the Web. ITAT 2017 Information Technologies - Applications and Theory, Martinské hole, Slovakia, 2017: CreateSpace Independent Publishing Platform, ISBN 978-1974274741, 2017, 218-222.
  15. M. Vaško, T. Jakab, T. Horváth: Recommendation in location-based and event-based social networks. 10th Workshop on Intelligent and Knowledge oriented Technologies, Košice, Slovakia, 2015.
  16. Š. Bocko, T. Horváth: Web-based Data Mining Assistant. Information Technologies - Applications and Theory, Part II: Proceedings of the 14th conference ITAT 2014 - Workshops and Posters, Jasná, Slovakia, ISBN 978-8087136195, 2014, p: 2-3.
  17. A. Busche, R. Janning, T. Horváth and L. Schmidt-Thieme: Some Improvements for Multi-Hyperbola Detection on GPR Data. Accepted to the LWA 2012 Conference of the joint forum of four special interest groups of the German Computer Science Society, Dortmund, Germany, 2012.
  18. L. Drumond, N. Thai-Nghe, T. Horváth, L. Schmidt-Thieme: Factorization Techniques for Student Performance Classification and Ranking. In Workshop and Poster Proceedings of the 20th Conference on User Modeling, Adaptation, and Personalization (UMAP'12), Montreal, Canada, 2012: CEUR Workshop Proceedings Vol-872, ISSN 1613-0073, 2012.
  19. N. Thai-Nghe, L. Drumond, T. Horváth, L. Schmidt-Thieme: Using Factorization Machines for Student Modeling. In Workshop and Poster Proceedings of the 20th Conference on User Modeling, Adaptation, and Personalization (UMAP'12), Montreal, Canada, 2012: CEUR Workshop Proceedings Vol-872, ISSN 1613-0073, 2012.
  20. N. Thai-Nghe, L. Drumond, T. Horváth, L. Schmidt-Thieme: Multi-Relational Matrix Factorization Models for Predicting Student Performance. In KDD 2011 Workshop on Knowledge Discovery in Educational Data (KDDinED 2011).
  21. N. Thai-Nghe, T. Horváth, L. Schmidt-Thieme: Context-Aware Factorization for Personalized Student's Task Recommendation. International Workshop on Personalization Approaches in Learning Environments (PALE 2011) at UMAP 2011, CEUR-WS, Volume 732, ISSN 1613-0073, p: 13-18.
  22. A. Eckhardt, T. Horváth, D. Marušcák, R. Novotný, P. Vojtáš: Uncertainty Issues in Automating Process Connecting Web and User. In: Proceedings of Workshop on Uncertainty Reasoning for the Semantic Web (URSW '07) - Volume 3, at 6th International Semantic Web Conference, Busan, Korea, 2007, (P. da Costa ed.), p: 97-108.
  23. T. Horváth: Reasons of Using IGAP to User Preference Learning. In: Proceedings of Workshop on Tools for Acquisition, Organization and Presenting of Information and Knowledge (2) NAZOU 2007, Poľana, Slovakia, 2007: Vydavatelstvo STU. Bratislava, Slovakia, 2007, ISBN 978-80-227-2716-7, p: 92-106.
  24. T. Horváth: Unsupervised Learning of User Preferences by Ordinal Classification. In: Proceedings of Workshop on Tools for Acquisition, Organization and Presenting of Information and Knowledge NAZOU 2006, Bystra Dolina, Slovakia, 2006: Vydavatelstvo STU. Bratislava, Slovakia, 2006, ISBN 80-227-2468-8, p:125-134.
  25. J. Bella, T. Horváth, P. Gurský, V. Vanekova: Fuzzy RDF in the Semantic Web: Deduction and Induction. In: 6th Slovak-Austrian Student Workshop WDA '05, Abaújszántó, Hungary, 2005: Elfa Academic Press, Ltd. Košice, Slovakia, 2005, ISBN 80-8086-015-7, p:16-29.
  26. T. Horváth, P. Vojtáš: GAP - Rule Discovery for Graded Classifciation. In: Workshop of Advances in Inductive Rule Learning (W8) of the 15th European Conference on Machine Learning and the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD '04), Pisa, Italy, 2004: TU Darmstadt (J. Fuernkranz eds.), Darmstadt, Germany, 2004, p:46-63.
  27. T. Horváth, F. Sudzina: Measuring impact of information systems on business competitiveness using regression and ILP. In: Ekonomika firiem, Michalovce, Slovakia, 2004: Podnikovohospodárska fakulta Ekonomickej univerzity v Bratislave so sídlom v Košiciach, Košice, Slovakia, 2004, ISBN 80-225-1879-4, p:296-300.
  28. T. Horváth, F. Sudzina: Introduction to data mining for managers. In: Application of Management Theory in Practice II, Košice, Slovakia, 2004: Royal Unicorn s.r.o., Košice, Slovakia, 2004, ISBN 80-969181-0-9, p:68-74.

Posters/Abstracts

  1. A. Kamuzora, W. Skaf, E. Birihanu, J. S. Mahmud, P. Kiss, T. Jursonovics, P. Pogrzeba, I. Lendák, T. Horváth: Matrix Factorization for Cache Optimization in Content Delivery Networks (CDN). Poster proceedings of the 22nd Industrial Conference on Data Mining 2022, New York, USA: ibai-publishing, p: 1-10.
  2. K. Buza, T. Horváth: O-41 The role of warping window size in case of EEG classification. CLINICAL NEUROPSYCHOLOGY, Volume 130, Issue 7: Elsevier, 2019, ISSN 1388-2457, p. e34.
  3. Š. Pero, T. Horváth: Opinion-Driven Matrix Factorization for Rating Prediction: The UMAP’13 talk and the received feedbacks. In. ITAT 2013: Information Technologies - Applications and Theory (Workshops, Posters, and Tutorials), Donovaly, Slovakia, 2013, ISBN 9781490952086, p. 21.
  4. T. Horváth: Recommender Systems. Tutorial at the 11th conference Znalosti, Mikulov, Czech Republic, 2012, ISBN 978-80-7378-220-7, p. 3.
  5. A. Busche, R. Janning, T. Horváth and L. Schmidt-Thieme: A Unifying Framework for GPR Image Reconstruction. The book of abstracts of the 36th Annual Conference of the German Classification Society (GfKl) on Data Analysis, Machine Learning and Applications, Hildesheim, Germany, 2012, p. 110.
  6. T. Horváth, P. Vojtáš: Fuzzy Inductive Logic Programming. In. Proceedings of the 16th International Conference on Inductive Logic Programming (ILP '06)- Short Papers, Santiago de Compostela, Spain, 2006: UDC Press Service, Coruna, Spain, 2006, ISBN 84-9749-206-4, p: 101-103.
  7. T. Horváth, P. Vojtáš: Efficient induction for Monotone Graded Classifciation. In: Work in Progress Papers of the 14th International Conference on Inductive Logic Programming (ILP '04), Porto, Portugal, 2004: (R. Camacho, R. King, A. Srinivasan eds.), Porto, Portugal, p:52-56.

Papers/Posters/Abstracts written in Slovak

  1. T. Horváth: Precízne poľnohospodárstvo - nápady a predstavy vs. realita Invited talk at the Conference Data a Znalosti, Košice, Slovakia, 2019, ISBN 978-80-553-3354-0, p. 15.
  2. M. Dzuriš, T. Horváth: Model používatel’ových preferencií vo fazetovom prehliadači. (in Slovak) In Proceedings of the 10th Czech and Slovak conference on Information Technologies - Application and Theory (ITAT '10), Smrekovica, Slovakia, 2010: Pont s.r.o., Slovakia, 2010, ISBN 978-80-970179-3-4, p: 53-58.
  3. Š. Pero, T. Horváth: Winston: Asistent Dolovania Dat. (in Slovak) In Proceedings of the 9th Czech and Slovak conference on Information Technologies - Application and Theory (ITAT '09), Kráľova Studňa, Slovakia, 2009: Pont s.r.o., Slovakia, 2009, ISBN 978-80-970179-1-0, p: 111-112.
  4. T. Horváth: Použitie Indukcie Generalizovaných Anotovaných Programov v Recommender Systémoch na učenie užívateľových preferencií. (in Slovak) In: Proceedings of the 2nd Workshop on Intelligent and Knowledge oriented Technologies, Košice, Slovakia, 2007: Centre for Information Technologies, FEI, Technical University in Košice, Slovakia, 2007, ISBN 978-80-89284-10-8, p: 158-161.
  5. T. Horváth: Fuzzy ILP: prístupy a problémy. (in Slovak) In: 4th Conference ZNALOSTI '05, Stará Lesná, Slovakia, 2005: FEI VŠB-TU Ostrava, Czech Republic, 2005, ISBN 80-248-0755-6, p:202-209.
  6. T. Horváth, F. Sudzina, P. Vojtáš: Kvalitatívny data mining - aplikácia v manažmente. (in Slovak) In: Nové trendy v podnikovom manažmente, Ružín, Slovakia, 2005: Podnikovohospodárska fakulta Ekonomickej univerzity v Bratislave so sídlom v Košiciach, Košice, Slovakia, 2005, ISBN 80-969181-3-3, p:289-298.
  7. T. Horváth, P. Vojtáš: ILP pre riešenie stupňovaného klasifikačného problému. (in Slovak) In: 2nd Conference ZNALOSTI '03, Ostrava, Czech Republic, 2003: FEI VŠB-TU Ostrava, Czech Republic, 2003, ISBN 80-248-0229-5, p:232–241.

Technical Reports, arXiv.org papers

  1. R. G. Mantovani, T. Horváth, R. Cerri, S. Barbon Junior, J. Vanschoren, A.C.P.L.F. de Carvalho: An empirical study on hyperparameter tuning of decision trees. arXiv.org, cs.LG, 1812.02207, 2018.
  2. C. Ribeiro, C. Signorini, C. Reis, E. Silva, E. Teixeira, L. Pereira, F. Louzada, I. Gendriz, I. Blanco, J. Fiorucci, K. Huaranca, L. Nonato, L. Garcia, M. Rangel, M. Filho, N. Lofti, P. Hubert, R. Sampaio, T. Horváth, W. da Silva, Zhao Liang: Analysis of Soundscape Ecology Data. CEPID-CeMEAI II Brazilian Study Group with Industry Report: ICMC/USP - São Carlos/SP, Brasil, August 2016.

Theses

  1. T. Horváth: User Preference Learning by Induction of Fuzzy and Annotated Logic Programs. PhD. Thesis, Faculty of Science, Pavol Jozef Šafárik University, Košice, June 2008.
  2. T. Horváth: Induktívne logické programovanie a jeho fuzzy analógia. (in Slovak) RNDr. Thesis, ICS, Faculty of Science, Pavol Jozef Šafárik University, Košice, June 2003.
  3. T. Horváth: Induktívne logické programovanie. (in Slovak) M.Sc. Thesis, ICS, Faculty of Science, Pavol Jozef Šafárik University, Košice, May 2002.

Other

  1. T. Horváth: Supportive textbook for the course Semantics of Knowledge Systems. Pavol Jozef Šafárik University, Košice, Slovakia, 2008.

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