zbMATH — the first resource for mathematics

Geometry Search for the term Geometry in any field. Queries are case-independent.
Funct* Wildcard queries are specified by * (e.g. functions, functorial, etc.). Otherwise the search is exact.
"Topological group" Phrases (multi-words) should be set in "straight quotation marks".
au: Bourbaki & ti: Algebra Search for author and title. The and-operator & is default and can be omitted.
Chebyshev | Tschebyscheff The or-operator | allows to search for Chebyshev or Tschebyscheff.
"Quasi* map*" py: 1989 The resulting documents have publication year 1989.
so: Eur* J* Mat* Soc* cc: 14 Search for publications in a particular source with a Mathematics Subject Classification code (cc) in 14.
"Partial diff* eq*" ! elliptic The not-operator ! eliminates all results containing the word elliptic.
dt: b & au: Hilbert The document type is set to books; alternatively: j for journal articles, a for book articles.
py: 2000-2015 cc: (94A | 11T) Number ranges are accepted. Terms can be grouped within (parentheses).
la: chinese Find documents in a given language. ISO 639-1 language codes can also be used.

a & b logic and
a | b logic or
!ab logic not
abc* right wildcard
"ab c" phrase
(ab c) parentheses
any anywhere an internal document identifier
au author, editor ai internal author identifier
ti title la language
so source ab review, abstract
py publication year rv reviewer
cc MSC code ut uncontrolled term
dt document type (j: journal article; b: book; a: book article)
A general approach to attribute reduction in rough set theory. (English) Zbl 1118.68669
Summary: The concept of a consistent approximation representation space is introduced. Many types of information systems can be treated and unified as consistent approximation representation spaces. At the same time, under the framework of this space, the judgment theorem for determining consistent attribute set is established, from which we can obtain the approach to attribute reductions in information systems. Also, the characterizations of three important types of attribute sets (the core attribute set, the relative necessary attribute set and the unnecessary attribute set) are examined.
68T30Knowledge representation
[1]Pawlak Z. Rough sets. Int J Comp Inf Sci, 1982, 11: 341–356 · Zbl 0501.68053 · doi:10.1007/BF01001956
[2]Pawlak Z. Rough Sets – Theoretical Aspects of Reasoning about Data. Dordrecht: Kluwer Academic Publishers, 1991
[3]Kryszkiewicz M. Comparative study of alternative types of knowledge reduction in insistent systems. Int J Intel Syst, 2001, 16: 105–120 · doi:10.1002/1098-111X(200101)16:1<105::AID-INT8>3.0.CO;2-S
[4]Zhang W-X, Leung Y, Wu W-Z. Information Systems and Knowledge Discovery. Beijing: Science Press, 2003
[5]Beynon M. Reducts within the variable precision rough sets model: A further investigation. Eur J Oper Res, 2001, 134: 592–605 · Zbl 0984.90018 · doi:10.1016/S0377-2217(00)00280-0
[6]Zhang W-X, Mi J-S, Wu W-Z. Approaches to knowledge reductions in inconsistent systems. Int J Intel Syst, 2003, 18: 989–1000 · Zbl 1069.68606 · doi:10.1002/int.10128
[7]Qiu G-F, Li H-Z, Xu L-D, et al. A knowledge processing method for intelligent systems based on inclusion degree. Expert Syst, 2003, 20(4): 187–195 · Zbl 05653438 · doi:10.1111/1468-0394.00243
[8]Mi J-S, Wu W-Z, Zhang W-X. Approaches to knowledge reduction based on variable precision rough set model. Inf Sci, 2004, 159: 255–272 · Zbl 1076.68089 · doi:10.1016/j.ins.2003.07.004
[9]Zhang M, Wu W-Z. Knowledge reduction in information systems with fuzzy decisions. J Eng Math, 2003, 20(2): 53–58
[10]Leung Y, Wu W-Z, Zhang W-X. Knowledge acquisition in incomplete information systems: a rough set approach. Eur J Oper Res, 2006, 168(1): 164–180 · Zbl 1136.68528 · doi:10.1016/j.ejor.2004.03.032
[11]Wu W-Z, Zhang M, Li H-Z, et al. Knowledge reduction in random information systems via Dempster-Shafer theory of evidence. Inf Sci, 2005, 174(3–4): 143–164 · Zbl 1088.68169 · doi:10.1016/j.ins.2004.09.002
[12]Skowron A, Rauszwer C. The discernibility matrices and functions in information systems. In: Slowinski R, ed. Intelligent Decision Support: Handbook of Applications and Advances of the Rough Set Theory. Dordrecht: Kluwer Academic Publishers, 1992. 331–362