This paper examines the knowledge representation theory of granulations. The key strengths of rough set theory are its capabilities in representing and processing knowledge in table format. For general granulation such capabilities are unknown. For single level granulation, two initial theories have been proposed previously by one of the authors. In this paper, the theories are re-visited, a new and deeper analysis is presented: Granular information table is an incomplete representation, so computing with words is the main method of knowledge processing. However for symmetrical granulation, the pre-topological information table is a complete representation, so the knowledge processing can be formal.
|名字||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|其他||10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005|
|期間||8/31/05 → 9/3/05|
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science