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The updating methods of object-induced three-way concept in dynamic formal contexts

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Abstract

The methods for constructing concept lattices are vital topics in formal concept analysis. Most of the existing algorithms for constructing three-way concept lattice take care of the static formal contexts and can not deal with the dynamic data. To address this problem, we study the updating methods of object-induced three-way concept lattices for dynamic formal contexts. The main contributions of this paper are as follows: When adding attributes or objects, we propose the update methods for object-induced three-way concepts, and present two algorithms (called AAI and AAP) based on adding multiple attributes. And then, the updating methods of object-induced three-way concept are developed for the case of deleting objects or attributes, and the related algorithm (called DOP) is proposed when deleting objects. Finally, several groups of datasets are selected from UCI for comparative experiments. The experimental results exhibit that our algorithms are more effective and advantageous than the latest construction algorithms.

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References

  1. Andrews S (2009) In-close, a fast algorithm for computing formal concepts. Proc Int Conf Formal Concept Anal Berlin, Germany: Springer 2004:372–385

    Google Scholar 

  2. Chen YH, Yao YY (2008) A multiview approach for intelligent data analysis based on data operators. Inf Sci 178(1):1–20

    Article  MathSciNet  MATH  Google Scholar 

  3. Chu XL, Sun BZ, Huang Q C, Yan Z (2020) Preference degree-based multi-granularity sequential three-way group conflict decisions approach to the integration of tcm and western medicine. Comput Ind Eng 143:106393

  4. Dntsch I, Gediga G (2002) Modal-style operators in qualitative data analysis. In: Proceedings of the 2002 IEEE International Conference on Data Mining, pp 155–162

  5. Formica A (2012) Semantic web search based on rough sets and fuzzy formal concept analysis. Knowl-Based Syst 26(9):40–47

    Article  Google Scholar 

  6. Fujita H, Gaeta A, Loia V, Orciuoli F (2018) Resilience analysis of critical infrastructures: a cognitive approach based on granular computing. IEEE Trans Cybern 49(5):1835–1848

    Article  Google Scholar 

  7. Ganter B, Wille R (1999) Formal concept analysis: Mathematical foundations. Springer, Berlin

  8. Gao C, Zhou J, Miao DQ, Wen JJ, Yue X D (2021) Three-way decision with co-training for partially labeled data. Inf Sci 544:500–518

    Article  MathSciNet  MATH  Google Scholar 

  9. Hao F, Yang YX, Min GY, Loia V (2021) Incremental construction of three-way concept lattice for knowledge discovery in social networks. Inf Sci 578:257–280

    Article  MathSciNet  Google Scholar 

  10. Klime J (2014) Using formal concept analysis for control in cyber-physical systems. Procedia Eng 69(1):1518–1522

    Article  Google Scholar 

  11. Lazer D, Kennedy R, King G, Vespignani A (2014) The parable of google flu: Traps in big data analysis. Science 343(6176):1203–1205

    Article  Google Scholar 

  12. Li B, Tian LY, Chen D Q, Han Y (2020) A task scheduling algorithm for phased-array radar based on dynamic three-way decision. Sensors 20(153):1–15

    Google Scholar 

  13. Liu KY, Li TR, Yang XB, Yang X, Liu D, Zhang PF, Wang J (2022) Granular cabin: An efficient solution to neighborhood learning in big data. Inf Sci 583:189–201

  14. Long BH, Xu WH, Zhang XY, Yang L (2020) The dynamic update method of attribute-induced three-way granular concept in formal contexts. Int J Approx Reason 126:228–248

    Article  MathSciNet  MATH  Google Scholar 

  15. Lv ZH, Qiao L (2020) Analysis of healthcare big data. Futur Gener Comput Syst 109:103–110

    Article  Google Scholar 

  16. Luo C, Li TR, Huang YY, Fujita H (2019) Updating three-way decisions in incomplete multi-scale information systems. Inf Sci 476:274–289

    Article  MATH  Google Scholar 

  17. Merwe D, Obiedkov S, Kourie D (2004) Addintent: a new incremental algorithm for constructing concept lattices. Lect Notes Artif Intell (Subser Lect Notes Comput Sci) 2961:372–385

    MATH  Google Scholar 

  18. Pawlak Z (1982) Rough set. Int J Comput Inf Sci 11(5):341–356

    Article  MATH  Google Scholar 

  19. Qi JJ, Qian T, Wei L (2016) The connections between three-way and classical concept lattices. Knowl-Based Syst 91:143–151

    Article  Google Scholar 

  20. Qi JJ, Wei L, Ren RS (2021) 3-Way concept analysis based on 3-Valued formal contexts. Cogn Comput:1–13

  21. Qi JJ, Wei L, Yao YY (2014) Three-way formal concept analysis. Rough Sets Knowl Technol:732–741

  22. Qian T, Wei L, Qi JJ (2017) Constructing three-way concept lattices based on apposition and subposition of formal contexts. Knowl-Based Syst 116(JAN.15):39–48

    Article  Google Scholar 

  23. Qian T, Wei L, Qi JJ (2019) A theoretical study on the object (property) oriented concept lattices based on three-way decisions. Soft Comput 23:9477–9489

    Article  MATH  Google Scholar 

  24. Ren RS, Wei L (2016) The attribute reductions of three-way concept lattices. Knowl-based Syst 99:92–102

    Article  Google Scholar 

  25. Sergei O, Sergei A (2002) Comparing performance of algorithms for generating concept lattices. J Exper Theor Artif Intell 14(2-3):189–216

    Article  MATH  Google Scholar 

  26. Shi R, Jiang CM (2022) Three-Way Ensemble prediction for workload in the data center. IEEE Access 10:10021–10030

    Article  Google Scholar 

  27. Silvia C, Elie S (2010) Object-fuzzy concept network: an enrichment of ontologies in semantic information retrieval. J Amer Soc Inform Sci Technol 59(13):2171–2185

    Google Scholar 

  28. Wei L, Liu L, Qi JJ, Qian T (2020) Rules acquisition of formal decision contexts based on three-way concept lattices. Inf Sci 516:529–544

    Article  MathSciNet  MATH  Google Scholar 

  29. Wille R (1982) Restructuring lattice theory: an approach based on hierarchies of concepts. Orderd Sets D Reidel 83:445–470

    Article  MathSciNet  MATH  Google Scholar 

  30. Yang SC, Lu YN, Jia XY, Li WW (2020a) Constructing three-way concept lattice based on the composite of classical lattices. Int J Approx Reas 121:174–186

  31. Yang X, Li TR, Fujita H, Liu D (2019) A sequential three-way approach to multi-class decision. Int J Approx Reason 104:108–125

    Article  MathSciNet  MATH  Google Scholar 

  32. Yang X, Li TR, Fujita H, Liu D, Yao YY (2017) A unified model of sequential three-way decisions and multilevel incremental processing. Knowl-Based Syst 134(oct.15):172–188

    Article  Google Scholar 

  33. Yang XP, Li TJ, Tan AH (2020b) Three-way decisions in fuzzy incomplete information systems. Int J Mach Learn Cybern 11:667–674

  34. Yang Y, Hu JH, Liu YM, Chen XH (2019) A multiperiod hybrid decision support model for medical diagnosis and treatment based on similarities and three-way decision theory. Expert Syst 36(3):1–25

    Article  Google Scholar 

  35. Yao YY (2004) A comparative study of formal concept analysis and rough set theory in data analysis. Lect Notes Comput Sci 3066(1):59–68

    Article  MathSciNet  MATH  Google Scholar 

  36. Yao YY (2010) Three-way decisions with probabilistic rough sets. Inf Sci 180(3):341–353

    Article  MathSciNet  Google Scholar 

  37. Yao YY (2011) The superiority of three-way decisions in probabilistic rough set models. Inf Sci 181(6):1080–1096

    Article  MathSciNet  MATH  Google Scholar 

  38. Yao YY (2012) An outline of a theory of three-way decisions. Lect Notes Comput Sci 8171:16–27

    Article  Google Scholar 

  39. Yao YY (2020) Three-way granular computing, rough sets, and formal concept analysis. Int J Approx Reason 116:106–125

    Article  MathSciNet  MATH  Google Scholar 

  40. Ye J, Zhan JM, Sun BZ (2021) A three-way decision method based on fuzzy rough set models under incomplete environments. Inf Sci 577:22–48

    Article  MathSciNet  Google Scholar 

  41. Zheng P, Chen CH, Shang SY (2019) Towards an automatic engineering change management in smart product-service systems a dsm-based learning approach. Adv Eng Inform 39:203–213

    Article  Google Scholar 

  42. Zhi HL, Qi JJ (2022) Common-possible concept analysis: a granule description viewpoint. Appl Intell 52(3):2975–2986

    Article  Google Scholar 

  43. Zhi HL, Qi JJ, Qian T, Wei L (2019) Three-way dual concept analysis. Int J Approx Reason 114:151–165

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgment

This work has been partially supported by the National Natural Science Foundation of China (Grant No. 61976130).

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Correspondence to Qian Hu.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Hu, Q., Qin, K. & Yang, L. The updating methods of object-induced three-way concept in dynamic formal contexts. Appl Intell 53, 1826–1841 (2023). https://doi.org/10.1007/s10489-022-03646-6

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