On rule acquisition in decision formal contexts

Jinhai Li1, Changlin Mei1, Aswani Kumar Cherukuri2, Xiao Zhang1
1School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, People’s Republic of China
2School of Information Technology and Engineering, VIT University, Vellore, India

Tóm tắt

Từ khóa


Tài liệu tham khảo

Wille R (1982) Restructuring lattice theory: an approach based on hierarchies of concepts. In: Rival I (ed) Ordered sets. Reidel, Dordrecht, pp 445–470

Zhang WX, Wei L, Qi JJ (2005) Attribute reduction theory and approach to concept lattice. Sci China Ser F 48(6):713–726

Liu M, Shao MW, Zhang WX, Wu C (2007) Reduction method for concept lattices based on rough set theory and its applications. Comput Math Appl 53(9):1390–1410

Wang X, Zhang WX (2008) Relations of attribute reduction between object and property oriented concept lattices. Knowl Based Syst 21:398–403

Medina J (2012) Relating attribute reduction in formal, object-oriented and property-oriented concept lattices. Comput Math Appl 64(6):1992–2002

Li TJ, Wu WZ (2011) Attribute reduction in formal contexts: a covering rough set approach. Fund Inform 111:15–32

Mi JS, Leung Y, Wu WZ (2010) Approaches to attribute reduction in concept lattices induced by axialities. Knowl Based Syst 23(6):504–511

Wei L, Qi JJ (2010) Relation between concept lattice reduction and rough set reduction. Knowl Based Syst 23(8):934–938

Cherukuri AK, Srinivas S (2010) Concept lattice reduction using fuzzy K-means clustering. Expert Syst Appl 37(3):2696–2704

Ganter B, Wille R (1999) Formal concept analysis: mathematical foundations. Springer, New York

Guigues JL, Duquenne V (1986) Famille minimales d’implications informatives résultant d’un tableau de données binaries. Math Sci Hum 95:5–18

Luxenburger M (1991) Implications partielles dans un contexte. Math Sci Hum 113:35–55

Dodin R, Missaoui R (1994) An incremental concept formation approach for learning from databases. Theor Comput Sci 133:387–419

Valtchev P, Missaoui R, Godin R (2004) Formal concept analysis for knowledge discovery and data mining: the new challenge. In: Proceedings of the 2004 international conference on formal concept analysis, Sydney, Australia, pp 352–371

Qu KS, Zhai YH (2008) Generating complete set of implications for formal contexts. Knowl Based Syst 21:429–433

Pasquier N, Bastide Y, Taouil R et al (1999) Efficient mining of association rules using closed itemset lattices. Inform Sci 24(1):25–46

Zaki MJ (2004) Mining non-redundant association rules. Data Min Knowl Disc 9:223–248

Cherukuri AK (2012) Fuzzy clustering based formal concept analysis for association rules mining. Appl Artif Intell 26(3):274–301

Zhang WX, Qiu GF (2005) Uncertain decision making based on rough sets. Tsinghua University Press, Beijing

Qu KS, Zhai YH, Liang JY et al (2007) Study of decision implications based on formal concept analysis. Int J Gen Syst 36(2):147–156

Shao MW (2007) Knowledge acquisition in decision formal contexts. In: Proceedings of the sixth international conference on machine learning and cybernetics, Hong Kong, pp 4050–4054

Wu WZ, Leung Y, Mi JS (2009) Granular computing and knowledge reduction in formal contexts. IEEE Trans Knowl Data Eng 21(10):1461–1474

Li J, Mei C, Lv Y (2011) A heuristic knowledge-reduction method for decision formal contexts. Comput Math Appl 61(4):1096–1106

Li J, Mei C, Lv Y (2011) Knowledge reduction in decision formal contexts. Knowl Based Syst 24(5):709–715

Li J, Mei C, Lv Y (2012) Knowledge reduction in formal decision contexts based on an order-preserving mapping. Int J Gen Syst 41(2):143–161

Song XX, Wang X, Zhang WX (2012) Independence of axiom sets characterizing formal concepts. Int J Mach Learn Cybern. doi: 10.1007/s13042-012-0110-z

Kent RE (1994) Rough concept analysis. In: Ziarko WP (ed) Rough sets, Fuzzy sets and knowledge discovery. Springer, London, pp 248–255

Yao YY (2004) Concept lattices in rough set theory. In: Proceedings of 2004 annual meeting of the north American fuzzy information processing society, Banff, Canada, pp 796–801

Düntsch I, Gediga G (2003) Approximation operators in qualitative data analysis. In: Swart H et al (eds) Theory and applications of relational structures as knowledge instruments, Lecture Notes in Computer Science, vol 2929. Springer, Berlin, pp 214–230

Wei L, Qi JJ, Zhang WX (2008) Attribute reduction theory of concept lattice based on decision formal contexts. Sci China Ser F 51(7):910–923

Pei D, Mi JS (2011) Attribute reduction in decision formal context based on homomorphism. Int J Mach Learn Cyber 2(4):289–293

Wang H, Zhang WX (2008) Approaches to knowledge reduction in generalized consistent decision formal contexts. Math Comput Model 48:1677–1684

Fielding AH (2007) Clustering and classification techniques for the biosciences. Cambridge University Press, London

Frank A, Asuncion A (2010) UCI machine learning repository [ http://archive.ics.uci.edu/ml ]. Irvine, CA: University of California, School of Information and Computer Science

Pei D, Li MZ, Mi JS (2011) Attribute reduction in fuzzy decision formal contexts. In: International conference on machine learning and cybernetics. IEEE Press, New York, pp 204–208

Li J, Mei C, Lv Y (2013) Incomplete decision contexts: approximate concept construction, rule acquisition and knowledge reduction. Int J Approx Reason 54(1):149–165

Li J, Mei C, Lv Y (2012) Knowledge reduction in real decision formal contexts. Inform Sci 189:191–207

Li J, Mei C, Lv Y, Zhang X (2012c) A heuristic knowledge reduction algorithm for real decision formal contexts. In: Yao JT et al (eds) Proceedings of RSCTC, Lecture Notes in Artificial Intelligence, vol 7413. Springer, Berlin, pp 303–312

Yang HZ, Leung Y, Shao MW (2011) Rule acquisition and attribute reduction in real decision formal contexts. Soft Comput 15(6):1115–1128