Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 5/2014

01-10-2014 | Original Article

An incremental approach to attribute reduction of dynamic set-valued information systems

Authors: Guangming Lang, Qingguo Li, Tian Yang

Published in: International Journal of Machine Learning and Cybernetics | Issue 5/2014

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Set-valued information systems are important generalizations of single-valued information systems. In this paper, three relations are proposed for attribute reduction of set-valued information systems. Then, we convert a large-scale set-valued information system into a smaller relation information system. An incremental algorithm is designed to compress dynamic set-valued information systems. Concretely, we mainly address the compression updating from three aspects: variations of attribute set, immigration and emigration of objects and alterations of attribute values. Finally, several illustrative examples are employed to demonstrate that attribute reduction of dynamic set-valued information systems are simplified significantly by our proposed approaches.
previous article A model integrating fuzzy AHP with QFD for assessing technical factors in aviation safety
next article Attribute reductions in object-oriented concept lattices

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Show more products
Literature
1.
2.
Bhatt RB, Gopal M (2005) On the compact computational domain of fuzzy-rough sets. Pattern Recognit Lett 26(11):1632–1640CrossRef
3.
Biswas R (1994) On rough sets and fuzzy rough sets. Bull Pol Acad Sci Math 42:345–349MATH
4.
5.
Capotorti A, Barbanera E (2012) Credit scoring analysis using a fuzzy probabilistic rough set model. Comput Stat Data Anal 56(4):981–994CrossRefMATHMathSciNet
6.
7.
Chen HM, Li TR, Qiao SJ, Ruan D (2010) A rough set based dynamic maintenance approach for approximations in coarsening and refining attribute values. Int J Intell Syst 25(10):1005–1026CrossRefMATH
8.
Chen ZC, Qin KY (2008) Attribute reduction of set-valued information system based on variable precision tolerance realtion. Comput Eng Appl 44: 27–29MathSciNet
9.
Chen ZC, Qin KY (2009) Attribute reduction of set-valued information system based on tolerance relation. Fuzzy Syst Math 23(1):150–154MATHMathSciNet
10.
11.
Dai JH, Tian HW (2013) Entropy measures and granularity measures for set-valued information systems. Inf Sci 240:72–82CrossRefMathSciNet
12.
13.
Dai JH, Wang WT, Tian HW, Liu L (2013) Attribute selection based on a new conditional entropy for incomplete decision systems. Knowl-Based Syst 39:207–213CrossRef
14.
15.
Dai JH, Xu Q (2013) Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification. Appl Soft Comput 13(1):211–221CrossRef
16.
17.
Dubois D, Prade H (1990) Rough fuzzy sets and fuzzy rough sets. Int J General Syst 17:191–209CrossRefMATH
18.
Feng T, Zhang SP, Mi JS, Feng Q (2011) Reductions of a fuzzy covering decision system. Int J Model Identif Control 13(3):225–233CrossRef
19.
20.
Grzymala-Busse JW (2010) Rough set and CART approaches to mining incomplete data. In: 2010 international conference of soft computing and pattern recognition (SoCPaR), Paris, pp 214–219
21.
Grzymala-Busse JW, Sedelow Jr. WA (1988) On rough sets and information system homomorphism. Bull Pol Acad Sci Tech Sci 36(3):233–239MATH
22.
23.
Huang B, Li HX, Wei DK (2012) Dominance-based rough set model in intuitionistic fuzzy information systems. Knowl-Based Syst 28: 115–123CrossRef
24.
Jensen R, Shen Q (2004) Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches. IEEE Trans Knowl Data Eng 16(12):1457–1471CrossRef
25.
Leung Y, Li DY (2003) Maximal consistent block technique for rule acquisition in incomplete information systems. Inf Sci 153:85–106CrossRefMATHMathSciNet
26.
Li SY, Li TR, Liu D (2013) Incremental updating approximations in dominance-based rough sets approach under the variation of the attribute set. Knowl Based Syst 40:17–26CrossRef
27.
Li DY, Ma YC (2000) Invariant characters of information systems under some homomorphisms. Inf Sci 129(1–4):211–220MATH
28.
Li TR, Ruan D, Geert W, Song J, Xu Y (2007) A rough sets based characteristic relation approach for dynamic attribute generalization in data mining. Knowl Based Syst 20(5):485–494CrossRef
29.
Liu CH, Miao DQ, Zhang N (2012) Graded rough set model based on two universes and its properties. Knowl Based Syst 33:65–72CrossRef
30.
Liu GL (2010) Rough set theory based on two universal sets and its applications. Knowl Based Syst 23(2):110–115CrossRef
31.
Liu PH, Chen ZC, Qin KY (2009) Attribute reduction of set-valued information systems based on maximal variable precision tolerance classes. J Sichuan Normal Univ 32(5):576–580MATH
32.
33.
Liu D, Li TR, Ruan D (2011) Probabilistic model criteria with decision-theoretic rough sets. Inf Sci 181:3709–3722CrossRefMathSciNet
34.
Liu D, Li TR, Ruan D, Zhang JB (2011) Incremental learning optimization on knowledge discovery in dynamic business intelligent systems. J Global Optim 51(2):325–344CrossRefMATHMathSciNet
35.
Liu D, Li TR, Ruan D, Zou WL (2009) An incremental approach for inducing knowledge from dynamic information systems. Fund Inf 94(2):245–260MATHMathSciNet
36.
37.
38.
Miao DQ, Gao C, Zhang N, Zhang ZF (2011) Diverse reduct subspaces based co-training for partially labeled data. Int J Approx Reason 52:1103–1117MathSciNet
39.
40.
41.
42.
43.
44.
45.
46.
Wang CZ, Wu CX, Chen DG (2008) A systematic study on attribute reduction with rough sets based on general binary relations. Inf Sci 178(9):2237–2261CrossRefMATHMathSciNet
47.
Wang SP, Zhu QX, Zhu W, Min F (2012) Matroidal structure of rough sets and its characterization to attribute reduction. Knowl Based Syst 36:155–161CrossRef
48.
Wang XZ, Tsang E, Zhao SY, Chen DG, Yeung D (2007) Learning fuzzy rules from fuzzy examples based on rough set techniques. Inf Sci 177(20):4493–4514CrossRefMATHMathSciNet
49.
Wang XZ, Zhai JH, Lu SX (2008) Induction of multiple fuzzy decision trees based on rough set technique. Inf Sci 178(16):3188–3202CrossRefMATHMathSciNet
50.
Yang T, Li QG (2010) Reduction about approximation spaces of covering generalized rough sets. Int J Approx Reason 51(3):335–345CrossRefMATH
51.
Yang XB, Song XN, Chen ZH, Yang JY (2012) On multigranulation rough sets in incomplete information system. Int J Mach Learn Cybern 3:223–232CrossRef
52.
Yang XB, Zhang M, Dou HL (2011) Neighborhood systems-based rough sets in incomplete information system. Knowl Based Syst 24(6):858–867CrossRef
53.
Yao YY (2003) Probabilistic approaches to rough sets. Expert Syst 20(5):287–297CrossRef
54.
Yao YY (2010) Three-way decisions with probabilistic rough sets. Inf Sci 180(3):341–353CrossRef
55.
56.
57.
Zhang JB, Li TR, Ruan D, Liu D (2012) Rough sets based matrix approaches with dynamic attribute variation in set-valued information systems. Int J Approx Reason 53(4):620–635CrossRefMATHMathSciNet
58.
Zhang JB, Li TR, Ruan D, Liu D (2012) Neighborhood rough sets for dynamic data mining. Int J Intell Syst 27:317-342CrossRef
59.
60.
Zhu, P (2011) Covering rough sets based on neighborhoods: An approach without using neighborhoods. Int J Approx Reason 52(3):461–472
61.
62.
Metadata
Title
An incremental approach to attribute reduction of dynamic set-valued information systems
Authors
Guangming Lang
Qingguo Li
Tian Yang
Publication date
01-10-2014
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 5/2014
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-013-0225-x

Other articles of this Issue 5/2014

International Journal of Machine Learning and Cybernetics 5/2014 Go to the issue

Original Article

Uncertainty measures in rough algebra with applications to rough logic

Original Article

An improved artificial bee colony algorithm for minimal time cost reduction

Original Article

Fuzzy neural control of uncertain chaotic systems with backlash nonlinearity

Original Article

Dual subspace learning via geodesic search on Stiefel manifold

Original Article

Interval-valued intuitionistic (T, S)-fuzzy filters theory on residuated lattices

Original Article

Attribute reductions in object-oriented concept lattices