Rough Sets: Introduction, History and Selected Applications (Tutorial Lecture — Extended Abstract)

• Autorzy: Dutta Soma , Ciucci Davide

Identyfikatory

DOI

10.15439/2023F0003

• Języki publikacji: EN

Abstrakty

EN

The aim of this tutorial is to present a brief overview of the theory of rough sets from the perspective of its mathematical foundations, history of development, as well as connections with other branches of mathematics and informatics. The content concerns both the theoretical and practical aspects of applications. The above mentioned target of the tutorial will be covered in two parts. In the first part we would aim to present the introduction to rough sets and the second part will focus on the connections with other branches of mathematics and informatics. In particular, in the second part, we will discuss the connections of rough sets with logics, topology and algebra, and graph theory (when it comes to mathematics), as well as knowledge representation, machine learning and data mining, and theoretical computer science (when it comes to informatics).

Słowa kluczowe

EN

computer science; rough sets; tutorials; mathematics; history; informatics

PL

informatyka; zbiory przybliżone; samouczek; matematyka; historia

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2023
• Tom: Vol. 35
• Strony: 69--70
• Opis fizyczny: Bibliogr. 15 poz.

Twórcy

autor

Dutta Soma

• University of Warmia and Mazury in Olsztyn Słoneczna 54, Olsztyn, Poland

autor

Ciucci Davide

• University of Milano-Bicocca viale Sarca 336/14, 20126, Milano, Italy

Bibliografia

• 1. Z. Pawlak, “Rough sets,” Int. J. Inform. Comput. Sci., vol. 11, pp. 341–356, 1982.
• 2. Z. Pawlak, Rough sets - theoretical aspects of reasoning about data, ser. Theory and decision library : series D. Kluwer, 1991, vol. 9.
• 3. E. Orlowska, “A logic of indiscernibility relations,” ser. Lecture Notes in Computer Sciences. Berlin: Springer-Verlag, 1985, no. 208, pp. 177–186.
• 4. D. Ciucci and D. Dubois, “Three-valued logics, uncertainty management and rough sets,” Trans. Rough Sets, vol. 17, pp. 1–32, 2014. [Online]. Available: https://doi.org/10.1007/978-3-642-54756-0_1
• 5. M. Banerjee, “Logic for rough truth,” Fundam. Informaticae, vol. 71, no. 2-3, pp. 139–151, 2006.
• 6. P. K. Singh and S. Tiwari, “Topological structures in rough set theory: A survey,” Hacettepe Journal of Mathematics and Statistics, vol. 49, no. 4, pp. 1270 – 1294, 2020.
• 7. G. Cattaneo and D. Ciucci, “Lattices with interior and closure operators and abstract approximation spaces,” Trans. Rough Sets, vol. 10, pp. 67–116, 2009.
• 8. G. Chiaselotti, D. Ciucci, T. Gentile, and F. Infusino, “Generalizations of rough set tools inspired by graph theory,” Fundam. Informaticae, vol. 148, no. 1-2, pp. 207–227, 2016.
• 9. M. Inuiguchi, W.-Z. Wu, C. Cornelis, and N. Verbiest, Fuzzy-Rough Hybridization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015, pp. 425–451.
• 10. A. Campagner, D. Ciucci, and T. Denoeux, “Belief functions and rough sets: Survey and new insights,” Int. J. Approx. Reason., vol. 143, pp. 192–215, 2022.
• 11. R. Bello and R. Falcon, Rough Sets in Machine Learning: A Review. Cham: Springer International Publishing, 2017, pp. 87–118.
• 12. D. Slezak, P. Synak, A. Wojna, and J. Wroblewski, “Two database related interpretations of rough approximations: Data organization and query execution,” Fundam. Informaticae, vol. 127, no. 1-4, pp. 445–459, 2013.
• 13. D. Bianucci and G. Cattaneo, “Information entropy and granulation coentropy of partitions and coverings: A summary,” Trans. Rough Sets, vol. 10, pp. 15–66, 2009.
• 14. D. Slęzak, “Approximate entropy reducts,” Fundam. Informaticae, vol. 53, no. 3-4, pp. 365–390, 2002.
• 15. A. Campagner, D. Ciucci, and V. Dorigatti, “Uncertainty representation in dynamical systems using rough set theory,” Theor. Comput. Sci., vol. 908, pp. 28–42, 2022.

Uwagi

1. Main Track Invited Contributions

2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).