@article{MTMT:34776900,
	title = {Intensions and extensions of granules: A two-component treatment},
	url = {https://m2.mtmt.hu/api/publication/34776900},
	author = {Mihálydeák, Tamás and Kádek, Tamás and Nagy, Dávid and Chakraborty, Mihir K.},
	doi = {10.1016/j.ijar.2024.109182},
	journal-iso = {INT J APPROX REASON},
	journal = {INTERNATIONAL JOURNAL OF APPROXIMATE REASONING},
	volume = {169},
	unique-id = {34776900},
	issn = {0888-613X},
	year = {2024},
	eissn = {1873-4731},
	pages = {1-15},
	orcid-numbers = {Kádek, Tamás/0000-0003-1865-5251}
}

@{MTMT:33830484,
	title = {Algebraic structures gained from rough approximation in incomplete information systems},
	url = {https://m2.mtmt.hu/api/publication/33830484},
	author = {Hannusch, Carolin and Mihálydeák, Tamás},
	booktitle = {Communication Papers of the 17th Conference on Computer Science and Intelligence Systems},
	doi = {10.15439/2022F90},
	unique-id = {33830484},
	year = {2022},
	pages = {73-77}
}

@article{MTMT:33573798,
	title = {Rough-Set-Like Approximation Spaces for Formal Languages},
	url = {https://m2.mtmt.hu/api/publication/33573798},
	author = {Battyányi, Péter and Mihálydeák, Tamás and Vaszil, György},
	doi = {10.25596/jalc-2022-079},
	journal-iso = {J AUTOM LANG COMB},
	journal = {JOURNAL OF AUTOMATA, LANGUAGES AND COMBINATORICS},
	volume = {27},
	unique-id = {33573798},
	issn = {1430-189X},
	year = {2022},
	eissn = {2567-3785},
	pages = {79-90}
}

@inproceedings{MTMT:32874830,
	title = {Logical Treatment of Incomplete/Uncertain Information Relying on Different Systems of Rough Sets},
	url = {https://m2.mtmt.hu/api/publication/32874830},
	author = {Mihálydeák, Tamás},
	booktitle = {Intelligence Science III},
	doi = {10.1007/978-3-030-74826-5_6},
	unique-id = {32874830},
	abstract = {The different systems of rough set theory treat uncertainty in special ways. There is a very important common property: all systems rely on given background knowledge and we cannot say more about an arbitrary set or about its members than its lower and upper approximations make possible. New membership relations have to be introduced. The semantics of classical logic is based on classical set theory. An important question: Is it possible to build logical systems with semantics relying on different versions of the theory of rough sets by using new membership relations? The paper gives an overview of first-order logical systems with partial semantics in order to show the influence of incomplete/uncertain information in logically valid inferences.},
	keywords = {Multivalued logic; Rough Sets Theory; Partial first-order logic},
	year = {2021},
	pages = {66-78}
}

@inproceedings{MTMT:32055117,
	title = {Similarity-Based Rough Sets with Annotation Using Deep Learning},
	url = {https://m2.mtmt.hu/api/publication/32055117},
	author = {Nagy, Dávid and Mihálydeák, Tamás and Kádek, Tamás},
	booktitle = {Intelligence Science III},
	doi = {10.1007/978-3-030-74826-5_8},
	unique-id = {32055117},
	year = {2021},
	pages = {93-102},
	orcid-numbers = {Kádek, Tamás/0000-0003-1865-5251}
}

@article{MTMT:32049481,
	title = {Dealing with uncertainty: A rough-set-based approach with the background of classical logic},
	url = {https://m2.mtmt.hu/api/publication/32049481},
	author = {Kádek, Tamás and Mihálydeák, Tamás},
	doi = {10.33039/ami.2021.02.005},
	journal-iso = {ANN MATH INFORM},
	journal = {ANNALES MATHEMATICAE ET INFORMATICAE},
	volume = {53},
	unique-id = {32049481},
	issn = {1787-5021},
	year = {2021},
	eissn = {1787-6117},
	pages = {157-168},
	orcid-numbers = {Kádek, Tamás/0000-0003-1865-5251}
}

@inproceedings{MTMT:31635889,
	title = {Similarity Based Granules},
	url = {https://m2.mtmt.hu/api/publication/31635889},
	author = {Nagy, Dávid and Mihálydeák, Tamás and Kádek, Tamás},
	booktitle = {Rough Sets},
	doi = {10.1007/978-3-030-52705-1_3},
	unique-id = {31635889},
	year = {2020},
	pages = {35-47},
	orcid-numbers = {Kádek, Tamás/0000-0003-1865-5251}
}

@article{MTMT:31401245,
	title = {Graph Approximation on Similarity Based Rough Sets},
	url = {https://m2.mtmt.hu/api/publication/31401245},
	author = {Nagy, Dávid and Mihálydeák, Tamás and Aszalós, László},
	doi = {10.1556/606.2020.15.2.3},
	journal-iso = {POLLACK PERIODICA},
	journal = {POLLACK PERIODICA: AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES},
	volume = {15},
	unique-id = {31401245},
	issn = {1788-1994},
	abstract = {Correlation clustering is a widely used technique in data mining. The clusters contain objects, which are typically similar to one another and different from objects from other groups. In the authors previous works the possible usage of correlation in rough set theory were investigated. In rough set theory, two objects are treated as indiscernible if all of their attribute values are the same. A base set contains those objects that are indiscernible from one another. The partition, gained from the correlation clustering, can be understood as the system of base sets, as the clusters contain the typically similar objects (not just to a distinguished member) and it considers the real similarity among the objects. In this work the extension of this study is presented, using the method to approximate graphs representing similarity relations.},
	year = {2020},
	eissn = {1788-3911},
	pages = {25-36}
}

@inproceedings{MTMT:30843033,
	title = {Generalized Membrane Systems with Dynamical Structure, Petri Nets, and Multiset Approximation Spaces},
	url = {https://m2.mtmt.hu/api/publication/30843033},
	author = {Battyányi, Péter and Mihálydeák, Tamás and Vaszil, György},
	booktitle = {Unconventional Computation and Natural Computation},
	doi = {10.1007/978-3-030-19311-9_3},
	volume = {11493 LNCS},
	unique-id = {30843033},
	year = {2019},
	pages = {15-29}
}

@article{MTMT:30705802,
	title = {Finding the representative in a cluster using correlation clustering},
	url = {https://m2.mtmt.hu/api/publication/30705802},
	author = {Nagy, Dávid and Aszalós, László and Mihálydeák, Tamás},
	doi = {10.1556/606.2019.14.1.2},
	journal-iso = {POLLACK PERIODICA},
	journal = {POLLACK PERIODICA: AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES},
	volume = {14},
	unique-id = {30705802},
	issn = {1788-1994},
	year = {2019},
	eissn = {1788-3911},
	pages = {15-24}
}