DocumentCode
3029084
Title
Fuzziness from attribute generalization in information table
Author
Tsumoto, Shusaku ; Hirano, Shoji
Author_Institution
Dept. of Med. Inf., Shimane Univ., Izumo
fYear
2008
fDate
14-16 Aug. 2008
Firstpage
455
Lastpage
461
Abstract
This paper shows some problems with combination of rule induction and attribute-oriented generalization, where if a given hierarchy includes inconsistencies, then application of hierarchical knowledge generates inconsistent rules, due to generation of fuzziness. Then, we propose an approach to solving this problem by using fuzzy linguistic variables. Also, this approach suggests that combination of rule induction and attribute-oriented generalization can be used to validate concept hierarchy.
Keywords
fuzzy set theory; generalisation (artificial intelligence); knowledge based systems; attribute generalization; attribute-oriented generalization; fuzzy linguistic variables; hierarchical knowledge; inconsistent rules; information table; rule induction; Biomedical informatics; Cognitive informatics; Context modeling; Data mining; Databases; Fuzzy sets; Induction generators; Information systems; Research and development; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics, 2008. ICCI 2008. 7th IEEE International Conference on
Conference_Location
Stanford, CA
Print_ISBN
978-1-4244-2538-9
Type
conf
DOI
10.1109/COGINF.2008.4639201
Filename
4639201
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