DocumentCode :
3231425
Title :
Fuzzy Many-Valued Context Analysis Based on Formal Description
Author :
Yan, Wang ; Baoxiang, Cao
Author_Institution :
Qufu Normal Univ., Rizhao
Volume :
3
fYear :
2007
fDate :
July 30 2007-Aug. 1 2007
Firstpage :
888
Lastpage :
892
Abstract :
Formal concept analysis (FCA) is an effective formal tool for data analysis. However, when FCA is applied to documents knowledge discovery, there are many situations in which uncertainty information also occurs. This paper proposed an approach to fuzzy many-valued context analysis by using formal descriptions instead of scaling. Within this approach, we extended the many-valued context by using the theory of fuzzy set. It certainly does not provide a better analysis than scaling, but it allows to do document knowledge discovery with the theory of FCA and to reduce the complexity of fuzzy concept lattice by using the conjunction and disjunction of confidence thresholds of different attributes.
Keywords :
data analysis; data mining; document handling; fuzzy set theory; data analysis; documents knowledge discovery; formal concept analysis; formal description; fuzzy concept lattice; fuzzy many-valued context analysis; fuzzy set theory; Artificial intelligence; Computer science; Constraint theory; Data analysis; Educational institutions; Fuzzy set theory; Fuzzy sets; Lattices; Software engineering; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-0-7695-2909-7
Type :
conf
DOI :
10.1109/SNPD.2007.35
Filename :
4287974
Link To Document :
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