A logic approach to granular computing

International Journal of Cognitive Informatics and Natural Intelligence

Volumn 2, Issue 2, 2008, Pages 63-79

  Zhou, Bing ^a   Yao, Yiyu ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

Formal concept analysis; Granular computing; Knowledge structure; Rough set analysis

Indexed keywords

COMPUTATION THEORY; COMPUTER CIRCUITS; GRANULAR COMPUTING; GRANULATION; HEURISTIC METHODS; INFORMATION ANALYSIS; ROUGH SET THEORY;

BUILDING BLOCKES; FORMAL CONCEPT ANALYSES (FCA); GRANULAR STRUCTURESS; HUMAN PROBLEM SOLVING; KNOWLEDGE STRUCTURES; LOGIC LANGUAGES; MULTIPLE LEVELS; ROUGH SET ANALYSIS;

FORMAL CONCEPT ANALYSIS;

EID: 58049099348     PISSN: 15573958     EISSN: 15573966     Source Type: Journal    
DOI: 10.4018/jcini.2008040104     Document Type: Article

References (37)

1. Bargiela, A., & Pedrycz, W. (2002). Granular computing: An introduction. Boston: Kluwer Academic.
2. Chen, Y. H., & Yao, Y. Y. (2007). A multiview approach for intelligent data analysis based on data operators. Information Sciences, 178(1), 1-20.
3. Demri, S., & Orlowska, E. (1997). Logical analysis of indiscernibility. In E. Orlowska (Ed.), Incomplete information: Rough set analysis (pp. 347-380). Heidelberg, Germany: Physica-Verlag.
4. Falmagne, J.-C., Koppen, M., Villano, M., Doignon, J.-P., & Johannesen, L. (1990). Introduction to knowledge spaces: How to build, test and search them. Psychological Review, 201-224.
5. Ganter, B., & Wille, R. (1999). Formal concept analysis, mathematical foundations. Berlin, Germany: Springer.
6. Grzymala-Busse, J. W. (2005). Incomplete data and generalization of indiscernibility relation, definability, and approximations. In Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, Proceedings of the 10th International Conference (LNAI 3641, pp. 244-253).
7. Lin, T. Y., Yao, Y. Y. & Zadeh, L. A. (Eds.). (2002). Data mining, rough sets and granular computing. Heidelberg, Germany: Physica-Verlag.
8. Marr, D. (1982). Vision, a computational investigation into human representation and processing of visual information. San Francisco: W. H. Freeman.
9. Nguyen, H. S., Skowron, A., & Stepaniuk, J. (2001). Granular computing: A rough set approach, Computational Intelligence, 17, 514-544.
10. Pawlak, Z. (1991). Rough sets-Theoretical aspects of reasoning about data. Boston: Kluwer Publishers.
11. Pawlak, Z., & Skowron, A. (2007). A. Rough sets: Some extensions. Information Science, 177, 28-40.
12. Quinlan, J. R. (1983). Learning efficient classification procedures and their application to chess end-games. In J. S. Michalski et al. (Eds.), Machine learning: An artificial intelligence approach (pp. 463-482). Morgan Kaufmann.
13. Simon, H. A., & Kaplan, C. A. (1989). Foundations of cognitive science. In M. I. Posner (Ed.), Foundations of cognitive science (pp. 1-47). Cambridge, MA: The MIT Press.
14. Smith, E. E. (1989). Concepts and induction. In M. I. Posner (Ed.), Foundations of cognitive science (pp. 501-526). Cambridge, MA: The MIT Press.
15. Sowa, J. F. (1984). Conceptual structures, information processing in mind and machine. Reading, MA: Addison-Wesley.
16. Van Mechelen, I., Hampton, J., Michalski, R. S., & Theuns, P. (Eds.). (1993). Categories and concepts, theoretical views and inductive data analysis. New York: Academic Press.
17. Wang, Y. (2003a). Cognitive informatics: A new transdisciplinary research field. Brain and Mind: A Transdisciplinary Journal of Neuroscience and Neurophilosophy, 4(2), 115-127.
18. Wang, Y. (2003b). On cognitive informatics. Brain and Mind: A Transdisciplinary Journal of Neuroscience and Neurophilosophy, 4(2), 151-167.
19. Wang, Y. (2007a). Software engineering foundations: A software science perspective. Auerbach Publications, NY., July.
20. Wang, Y. (2007b). The theoretical framework of cognitive informatics. The International Journal of Cognitive Informatics and Natural Intelligence, 1(1), 1-27.
21. Wille, R. (1982). Restructuring lattice theory: An approach based on hierarchies of concepts.. In I. Rival (Ed.), Ordered sets (pp. 445-470). Boston: Reidel, Dordrecht.
22. Wille, R. (1992). Concept lattices and conceptual knowledge systems. Computers Mathematics with Applications, 23, 493-515.
23. Yao, J.T. (2007). A ten-year review of granular computing. In Proceedings of the 3rd IEEE International Conference on Granular Computing (pp. 299-302).
24. Yao, Y. Y. (2001a). Information granulation and rough set approximation. International Journal of Intelligent Systems, 16, 87-104.
25. Yao, Y. Y. (2001b). Modeling data mining with granular computing. In Proceedings of the 25th Annual International Computer Software and Applications Conference (pp. 638-643).
26. Yao, Y. Y. (2004a). A comparative study of formal concept analysis and rough set theory in data analysis. In International Conference on Rough Sets and Current Trends in Computing (RSCTC'2004) (pp. 59-68).
27. Yao, Y. Y. (2004b). Concept formation and learning: A cognitive informatics perspective. In Proceedings of the Thi rd IEEE International Conference on Cognitive Informatics.
28. Yao, Y. Y. (2004c). Granular computing. In Proceedings of the Fourth Chinese National Conference on Rough Sets and Soft Computing (pp. 1-5).
29. Yao, Y.Y. (2004d). A partition model of granular computing. LNCS transactions on rough sets (LNCS 3100, pp. 232-253).
30. Yao, Y. Y. (2006a). Granular computing and cognitive informatics. In Proceedings of the Fifth IEEE International Conference on Cognitive Informatics (pp. 17-18).
31. Yao, Y. Y. (2006b). Three perspectives of granular computing. In Proceedings, International Forum on Theory of GrC from Rough Set Perspective, Journal of Nanchang Institute of Technology (pp. 16-21).
32. Yao, Y. Y. (2007a). The art of granular computing. In Proceeding of the International Conference on Rough Sets and Emerging Intelligent Systems Paradigms (LNAI, 4585, pp. 101-112).
33. Yao, Y. Y. (2007b). A note on definability and approximations. In Transactions on rough sets (pp. 274-282).
34. Yao, Y. Y., & Liau, C.-J. (2002). A generalized decision logic language for granular computing. In FUZZ-IEEE'02 in the 2002 IEEE World Congress on Computational Intelligence (pp. 1092-1097).
35. Yao, Y. Y., & Zhou, B. (2007). A logic language of granular computing. In Proceedings of the Sixth IEEE International Conference on Cognitive Informatics (pp. 178-185).
36. Yao, Y. Y., Zhou, B., & Chen, Y. H. (2007). Interpreting low and high order rules: A granular computing approach. In Proceedings of International Conference on Rough Sets and Emerging Intelligent System Paradigms (RSEISP'07) (LNAI 4585, pp. 371-380).
37. Zadeh, L. A. (1997). Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems, 19, 111-127.