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International Joint Conference on Rough Sets

IJCRS 2019: Rough Sets pp 534–548Cite as

A Bibliometric Profile of Research on Rough Sets

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11499))

Abstract

Rough sets theory is a powerful mathematical tool for modelling various types of inexact, incomplete or uncertain information. Rough sets theory and its applications have attracted significant attention among researchers and extensive research has been carried out since it was first proposed by Pawlak in 1982. This paper presents a panorama of rough sets and quantitatively analyzes the developments of rough sets research by scientometrics approach. The bibliometric analysis is conducted based on 11833 Web of Science indexed papers published from 1982 to 2018. The science mapping tool, VOSviewer, is employed to cluster the documents and to assist in summarizing the important publications over the last ten years. The results are presented in the following aspects: development stages over the recent two decades, thematic structure of publications, citation distribution on subjects, core journals and conferences, international research collaboration profiles and top scholars. The results can benefit the scholars who want to go further in future research of rough sets.

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References

  1. Ma, X., Zhan, J., Ali, M.I., Mehmood, N.: A survey of decision making methods based on two classes of hybrid soft set models. Artif. Intell. Rev. 49(4), 511–529 (2018)

    Article  Google Scholar 

  2. Pawlak, Z., Skowron, A.: Rudiments of rough sets. Inf. Sci. 177(1), 3–27 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  3. Zavadskas, E.K., Turskis, Z.: Multiple criteria decision making (MCDM) methods in economics: an overview/Daugiatiksliai sprendimu priemimo metodai ekonomikoje: apzvalga. Technol. Econ. Dev. Econ. 17(2), 397–427 (2011)

    Article  Google Scholar 

  4. Karanatsiou, D., Li, Y.H., Arvanitou, E.M., Misirlis, N., Wong, W.E.: A bibliometric assessment of software engineering scholars and institutions (2010–2017). J. Syst. Softw. 147, 246–261 (2019)

    Article  Google Scholar 

  5. Wang, X.Y., Tang, B.J.: Review of comparative studies on market mechanisms for carbon emission reduction: a bibliometric analysis. Nat. Hazards 94(3), 1141–1162 (2018)

    Article  Google Scholar 

  6. Wei, G.Y.: A bibliometric analysis of the top five economics journals during 2012–2016. J. Econ. Surv. 33(1), 25–59 (2019)

    Article  Google Scholar 

  7. Ferreira, F.A.F.: Mapping the field of arts-based management: Bibliographic coupling and co-citation analyses. J. Bus. Res. 85, 348–357 (2018)

    Article  Google Scholar 

  8. Blanco-Mesa, F., Lindahl, J.M.M., Gil-Lafuente, A.M.: A bibliometric analysis of fuzzy decision making research, pp. 1–4 (2016)

    Google Scholar 

  9. Jensen, R., Shen, Q.: New approaches to fuzzy-rough feature selection. IEEE Trans. Fuzzy Syst. 17(4), 824–838 (2009)

    Article  Google Scholar 

  10. Chen, Y.M., Miao, D.Q., Wang, R.Z.: A rough set approach to feature selection based on ant colony optimization. Pattern Recognit. Lett. 31(3), 226–233 (2010)

    Article  Google Scholar 

  11. Qian, Y., Liang, J., Pedrycz, W., Dang, C.: Positive approximation: an accelerator for attribute reduction in rough set theory. Artif. Intell. 174(9), 597–618 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  12. Wang, C., Hu, Q., Wang, X., Chen, D., Qian, Y., Dong, Z.: Feature selection based on neighborhood discrimination index. IEEE Trans. Neural Netw. Learn. Syst. 29(7), 2986–2999 (2018)

    MathSciNet  Google Scholar 

  13. He, Y., Liao, N., Zhou, Y.: Analysis on provincial industrial energy efficiency and its influencing factors in China based on DEA-RS-FANN. Energy 142, 79–89 (2018)

    Article  Google Scholar 

  14. Cai, Z., He, Z., Guan, X., Li, Y.: Collective data-sanitization for preventing sensitive information inference attacks in social networks. IEEE Trans. Dependable Secure Comput. 15(4), 577–590 (2018)

    Google Scholar 

  15. Choudhary, A.K., Harding, J.A., Tiwari, M.K.: Data mining in manufacturing: a review based on the kind of knowledge. J. Intell. Manuf. 20(5), 501 (2008)

    Article  Google Scholar 

  16. Dubois, D., Prade, H.: Rough fuzzy sets and fuzzy rough sets. Int. J. Gen. Syst. 17(2–3), 191–209 (1990)

    Article  MATH  Google Scholar 

  17. Yao, Y.Y.: A comparative study of fuzzy sets and rough sets. Inf. Sci. 109(1), 227–242 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  18. Wu, W.-Z., Mi, J.-S., Zhang, W.-X.: Generalized fuzzy rough sets. Inf. Sci. 151, 263–282 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  19. Wu, W.-Z., Leung, Y., Mi, J.-S.: On characterizations of (I,T)-fuzzy rough approximation operators. Fuzzy Sets Syst. 154(1), 76–102 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  20. Yeung, D.S., Degang, C., Tsang, E.C.C., Lee, J.W.T., Wang, X.: On the generalization of fuzzy rough sets. IEEE Trans. Fuzzy Syst. 13(3), 343–361 (2005)

    Article  Google Scholar 

  21. Hu, Q., Xie, Z., Yu, D.: Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation. Pattern Recognit. 40(12), 3509–3521 (2007)

    Article  MATH  Google Scholar 

  22. Mi, J.-S., Zhang, W.-X.: An axiomatic characterization of a fuzzy generalization of rough sets. Inf. Sci. 160(1), 235–249 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  23. Molodtsov, D.: Soft set theory - first results. Comput. Math. Appl. 37(4–5), 19–31 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  24. Maji, P.K., Roy, A.R., Biswas, R.: An application of soft sets in a decision making problem. Comput. Math. Appl. 44(8), 1077–1083 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  25. Chen, D., Tsang, E.C.C., Yeung, D.S., Wang, X.: The parameterization reduction of soft sets and its applications. Comput. Math. Appl. 49(5), 757–763 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  26. Aktaş, H., Çağman, N.: Soft sets and soft groups. Inf. Sci. 177(13), 2726–2735 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  27. Feng, F., Li, C., Davvaz, B., Ali, M.I.: Soft sets combined with fuzzy sets and rough sets: a tentative approach. Soft Comput. 14(9), 899–911 (2010)

    Article  MATH  Google Scholar 

  28. Ma, X., Liu, Q., Zhan, J.: A survey of decision making methods based on certain hybrid soft set models. Artif. Intell. Rev. 47(4), 507–530 (2017)

    Article  Google Scholar 

  29. Feng, F., Liu, X., Leoreanu-Fotea, V., Jun, Y.B.: Soft sets and soft rough sets. Inf. Sci. 181(6), 1125–1137 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  30. Zhan, J., Liu, Q., Herawan, T.: A novel soft rough set: soft rough hemirings and corresponding multicriteria group decision making. Appl. Soft Comput. 54, 393–402 (2017)

    Article  Google Scholar 

  31. Zhan, J., Zhu, K.: A novel soft rough fuzzy set: Z-soft rough fuzzy ideals of hemirings and corresponding decision making. Soft Comput. 21(8), 1923–1936 (2017)

    Article  MATH  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  34. Li, H., Zhou, X.: Risk decision making based on decision-theoretic rough set: a three-way view decision model. Int. J. Comput. Intell. Syst. 4(1), 1–11 (2011)

    Article  MathSciNet  Google Scholar 

  35. Herbert, J.P., Yao, J.T.: Game-theoretic rough sets. Fundam. Informat. 108(3–4), 267–286 (2011)

    MathSciNet  MATH  Google Scholar 

  36. Sun, B., Ma, W., Xiao, X.: Three-way group decision making based on multigranulation fuzzy decision-theoretic rough set over two universes. Int. J. Approx. Reason. 81, 87–102 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  37. Li, J., Huang, C., Qi, J., Qian, Y., Liu, W.: Three-way cognitive concept learning via multi-granularity. Inf. Sci. 378, 244–263 (2017)

    Article  Google Scholar 

  38. Li, H., Zhang, L., Huang, B., Zhou, X.: Sequential three-way decision and granulation for cost-sensitive face recognition. Knowl. Based Syst. 91, 241–251 (2016)

    Article  Google Scholar 

  39. Zhang, H.-R., Min, F., Shi, B.: Regression-based three-way recommendation. Inf. Sci. 378, 444–461 (2017)

    Article  Google Scholar 

  40. Yu, H., Liu, Z., Wang, G.: An automatic method to determine the number of clusters using decision-theoretic rough set. Int. J. Approx. Reason. 55(1), 101–115 (2014). Part 2

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  Google Scholar 

  42. Jia, X., Liao, W., Tang, Z., Shang, L.: Minimum cost attribute reduction in decision-theoretic rough set models. Inf. Sci. 219, 151–167 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  43. Zhu, W.: Relationship between generalized rough sets based on binary relation and covering. Inf. Sci. 179(3), 210–225 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  44. Zhang, X.H., Miao, D.Q., Liu, C.H., Le, M.L.: Constructive methods of rough approximation operators and multigranulation rough sets. Knowl. Based Syst. 91, 114–125 (2016)

    Article  Google Scholar 

  45. Qian, Y., Liang, J., Yao, Y., Dang, C.: MGRS: a multi-granulation rough set. Inf. Sci. 180(6), 949–970 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  46. Yang, X., Liang, S., Yu, H., Gao, S., Qian, Y.: Pseudo-label neighborhood rough set: measures and attribute reductions. Int. J. Approx. Reason. 105, 112–129 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  47. Wang, C., He, Q., Shao, M., Hu, Q.: Feature selection based on maximal neighborhood discernibility. Int. J. Mach. Learn. Cybern. 9(11), 1929–1940 (2018)

    Article  Google Scholar 

  48. Liu, B.H., Fu, Z.G., Wang, P.K., Liu, L., Gao, M.D., Liu, J.: Big-data-mining-based improved K-means algorithm for energy use analysis of coal-fired power plant units: a case study. Entropy 20(9), 702 (2018)

    Article  Google Scholar 

  49. Mazzorana, B., Trenkwalder-Platzer, H., Heiser, M., Hubl, J.: Quantifying the damage susceptibility to extreme events of mountain stream check dams using rough set analysis. J. Flood Risk Manag. 11(4), e12333 (2018)

    Article  Google Scholar 

  50. Juneja, A., Rana, B., Agrawal, R.K.: A novel fuzzy rough selection of non-linearly extracted features for schizophrenia diagnosis using fMRI. Comput. Methods Programs Biomed. 155, 139–152 (2018)

    Article  Google Scholar 

  51. Dey, S., Sultana, N., Dey, P., Pradhan, S.K., Datta, S.: Intelligent design optimization of age-hardenable Al alloys. Comput. Mater. Sci. 153, 315–325 (2018)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. College of Electronics and Information Engineering, Tongji University, Shanghai, 200092, China

    Wenjie Wei & Duoqian Miao

  2. Siping Campus Library, Tongji University, Shanghai, 200092, China

    Wenjie Wei

  3. School of Foreign Languages, Tongji University, Shanghai, 200092, China

    Yuxiang Li

Authors
  1. Wenjie Wei
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  2. Duoqian Miao
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  3. Yuxiang Li
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Corresponding author

Correspondence to Duoqian Miao .

Editor information

Editors and Affiliations

  1. University of Debrecen, Debrecen, Hungary

    Tamás Mihálydeák

  2. Southwest Petroleum University, Chengdu, China

    Fan Min

  3. Chongqing University of Posts and Telecommunications, Chongqing, China

    Guoyin Wang

  4. Indian Institute of Technology Kanpur, Kanpur, India

    Mohua Banerjee

  5. Fujian Normal University, Fuzhou, China

    Ivo Düntsch

  6. University of Rzeszów, Rzeszow, Poland

    Zbigniew Suraj

  7. University of Milano-Bicocca, Milan, Italy

    Davide Ciucci

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Wei, W., Miao, D., Li, Y. (2019). A Bibliometric Profile of Research on Rough Sets. In: Mihálydeák, T., et al. Rough Sets. IJCRS 2019. Lecture Notes in Computer Science(), vol 11499. Springer, Cham. https://doi.org/10.1007/978-3-030-22815-6_41

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  • DOI: https://doi.org/10.1007/978-3-030-22815-6_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22814-9

  • Online ISBN: 978-3-030-22815-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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