Computer Science ›› 2014, Vol. 41 ›› Issue (10): 244-248.doi: 10.11896/j.issn.1002-137X.2014.10.051

Previous Articles     Next Articles

Clustering Stability Analysis for Non-numeric Data Based on Concept Lattice

ZHI Hui-lai   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Stable concepts usually represent strong correlation with real world entities and the calculation of concept stability,which is proven as an NP-complete problem,plays an important role in clustering analysis.To precisely calculate concept stability,concept lattice was used as the analysis model.At first,the definition of kernel object set as well as the way to find the kernel object set of a concept was proposed,and then concept stability was calculated based on kernel object set.Meanwhile,the method of calculating kernel attribute set of a given concept was derived directly based on the principle of duality of concept lattice.At last,an example was given to illustrate the application of concept stability.

Key words: Formal concept analysis,Concept lattice,Clustering stability,Kernel object set

[1] Jain A K,Dubes R C.Algorithms for Clustering Data[M].Prentice Hall,1988
[2] Melo C,Le-Grand B,Aufaure M A,et al.Extracting and visualising tree-like structures from concept lattices[C]∥15th International Conference on Information Visualisation.London,Uni-ted Kingdom,IEEE Computer Society,2011:261-266
[3] Brito P,Polaillon G.Homogeneity and stability in conceptual analysis[C]∥Amedeo Napoli,Vilem Vychodil,eds.CLA,2011:251-263
[4] Kuznetsov S,Obiedkov S,Roth C.Reducing the representationcomplexity of lattice-based taxonomies[J].Conceptual Structures:Knowledge Architectures for Smart Applications Lecture Notes in Computer Science,2007,4:241-254
[5] Kuznetsov S O.On stability of a formal concept[J].Annals ofMathematics and Artificial Intelligence,2007,49(1-4):101-115
[6] Gan G,Wu J.Subspace clustering for high dimensional categorical data[J].ACM SIGKDD Explorations Newsletters,2004,6(2):87-94
[7] Zaki M,Peters M,Assent I,et al.CLICK:an effective algorithm for mining subspace clusters in categorical datasets[J].Data and Knowledge Engineering,2007(60):51-70
[8] Tang Cheng-long,Wang Shi-gang,Xu Wei.New fuzzy c-means clustering model based on the data weighted approach[J].Data & Knowledge Engineering,2010,9(9):881-900
[9] Bai Liang,Liang Ji-ye,Dang Chuang-yin,et al.A novel attribute weighting algorithm for clustering high-dimensional categorical data [J].Pattern Recognition,2011,44(12):2843-2861
[10] Ji Jin-chao,Pang Wei,Zhou Chun-guang,et al.A fuzzy k-prototype clustering algorithm for mixed numeric and categorical data[J].Knowledge-Based Systems,2012,30:129-135
[11] Wu Xin-dong,Zhang Cheng-qi,Zhang Shi-chao.Efficient mining of both positive and negative association rules[J].ACM Tran-sactions on Information Systems,2004,22(3):381-405
[12] Rosch E.Human categorization[C]∥Warren N,ed.Studies in Cross-Cultural Psychology.Academic press,New York,1977:1-49
[13] Ganter B,Wille R.Formal Concept Analysis:mathematical foundation [M].New York:Springer-Verlag,l999
[14] Scaife M,Rogers Y.External cognition:how do graphical representations work[J].International Journal of Human Computer Studies,1996,5:185-213
[15] 谢志鹏,刘宗田.概念格与关联规则发现[J].计算机研究与发展,2000,37(12):1415-1421
[16] Kuznetsov S O.Stability as an estimate of the degree of substantiation of hypotheses derived on the basis of operational similarity[J].Nauchn.Tekh.Inf.,Ser.2 (Automat.Document.Math.Linguist.),1990,2:21-29
[17] Kuznetsov S O,Obiedkov S.Comparing Performance of Algorithms for Generating Concept Lattices[J].Journal of Experimental and Theoretical Artificial Intelligence,2002(14):189-216
[18] Adams E N.Consensus techniques and the comparison of taxonomic trees[J].Systematic Zoology,1972,21:390-397

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!