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A scientometrics review on aggregation operator research

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Abstract

As one of the most important tool for information fusion, aggregation operator has successful application in decision making, combination forecasting, military operations research and so on. Therefore, the focus of this paper is to present in a scientometrics review on the development of aggregation operator. The records adopted in this paper were downloaded from Web of Science. The useful information visualization software called CiteSpace II was utilized to analysis and visualizes the development of the discipline of aggregation operator. According to the results of this study, the main research clusters of this area and their corresponding key elements can be revealed. The close relationship between the different clusters, main journals, and important authors can be found out and shown in a visualization and quantitative way. The research of this paper will become a significant reference source for theoretical researchers and practitioners working in the area of information fusion, decision making and operations research.

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References

  • Agryzkov, T., Oliver, J. L., Tortosa, L., & Vicent, J. (2014). A new betweenness centrality measure based on an algorithm for ranking the nodes of a network. Applied Mathematics and Computation, 244, 467–478.

    Article  MathSciNet  Google Scholar 

  • Ale Ebrahim, N., Salehi, H., Embi, M. A., Habibi, F., Gholizadeh, H., Motahar, S. M., & Ordi, A. (2013). Effective strategies for increasing citation frequency. International Education Studies, 6(11), 93–99.

    Article  Google Scholar 

  • Beliakov, G., Pradera, A., & Calvo, T. (2007). Aggregation functions: A guide for practitioners (Vol. 361). Heidelberg: Springer.

    Google Scholar 

  • Bui, C. C. (1999). On group decision making under linguistic assessments. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 7(04), 301–308.

    Article  MATH  Google Scholar 

  • Calvo, T., Mayor, G., & Mesiar, R. (Eds.). (2002). Aggregation operators: New trends and applications (Vol. 97). New York: Springer.

    Google Scholar 

  • Calvo, T., Mesiar, R., & Yager, R. R. (2004). Quantitative weights and aggregation. IEEE Transactions on Fuzzy Systems, 12(1), 62–69.

    Article  Google Scholar 

  • Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359–377.

    Article  Google Scholar 

  • Chen, C., Hu, Z., Liu, S., & Tseng, H. (2012). Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace. Expert Opinion on Biological Therapy, 12(5), 593–608.

    Article  Google Scholar 

  • Choi, D. Y. (1999). A new aggregation method in a fuzzy environment. Decision Support Systems, 25(1), 39–51.

    Article  Google Scholar 

  • Dubois, D., & Prade, H. (1985). A review of fuzzy set aggregation connectives. Information Sciences, 36(1), 85–121.

    Article  MATH  MathSciNet  Google Scholar 

  • Feng, F., Zhang, L., Du, Y., & Wang, W. (2015). Visualization and quantitative study in bibliographic databases: A case in the field of university–industry cooperation. Journal of Informetrics, 9(1), 118–134.

    Article  Google Scholar 

  • Fodor, J. C., & Roubens, M. R. (1994). Fuzzy preference modelling and multi-criteria decision support (Vol. 14). New York: Springer.

    Book  Google Scholar 

  • Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215–239.

    Article  Google Scholar 

  • Hadi-Vencheh, A., & Mirjaberi, M. (2014). Fuzzy inferior ratio method for multiple attribute decision making problems. Information Sciences, 277, 263–272.

    Article  MathSciNet  Google Scholar 

  • Heneberg, P. (2013). Effects of print publication lag in dual format journals on scientometric indicators. PLoS One, 8(4), e59877.

    Article  Google Scholar 

  • Herrera, F., & Martínez, L. (2000). A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems, 8(6), 746–752.

    Article  Google Scholar 

  • Hu, Y., Sun, J., Li, W., & Pan, Y. (2014). A scientometric study of global electric vehicle research. Scientometrics, 98(2), 1269–1282.

    Article  Google Scholar 

  • Kim, M. C., & Chen, C. (2015). A scientometric review of emerging trends and new developments in recommendation systems. Scientometrics, 104(1), 239–263.

    Article  Google Scholar 

  • Klir, G. J., & Folger, T. A. (1988). Fuzzy sets, uncertainty, and information. Upper Saddle River: Printice Hall.

    MATH  Google Scholar 

  • Leydesdorff, L. (2007). Visualization of the citation impact environments of scientific journals: An online mapping exercise. Journal of the American Society for Information Science and Technology, 58(1), 25–38.

    Article  Google Scholar 

  • Li, D. F. (2010). Linear programming method for MADM with interval-valued intuitionistic fuzzy sets. Expert Systems with Applications, 37(8), 5939–5945.

    Article  Google Scholar 

  • Liu, Z., Yin, Y., Liu, W., & Dunford, M. (2015). Visualizing the intellectual structure and evolution of innovation systems research: A bibliometric analysis. Scientometrics, 103(1), 135–158.

    Article  Google Scholar 

  • Merigo, J. M., & Casanovas, M. (2010). Induced and heavy aggregation operators with distance measures. Journal of Systems Engineering and Electronics, 21(3), 431–439.

    Article  MathSciNet  Google Scholar 

  • Morar, M., & Agachi, P. S. (2010). Review: Important contributions in development and improvement of the heat integration techniques. Computers and Chemical Engineering, 34(8), 1171–1179.

    Article  Google Scholar 

  • Narukawa, Y. (2007). Modeling decisions: Information fusion and aggregation operators. New York: Springer.

    Google Scholar 

  • Pedrycz, W., Ekel, P., & Parreiras, R. (2011). Fuzzy multi-criteria decision-making: Models, methods and applications. New York: Wiley.

    Google Scholar 

  • Qian, G. (2014). Scientometric sorting by importance for literatures on life cycle assessments and some related methodological discussions. The International Journal of Life Cycle Assessment, 19(7), 1462–1467.

    Article  Google Scholar 

  • Rickard, J. T., & Aisbett, J. (2014). New classes of threshold aggregation functions based upon the Tsallis q-exponential with applications to perceptual computing. IEEE Transactions on Fuzzy Systems, 22(3), 672–684.

    Article  Google Scholar 

  • Rojas, I., Ortega, J., Pelayo, F. J., & Prieto, A. (1999). Statistical analysis of the main parameters in the fuzzy inference process. Fuzzy Sets and Systems, 102(2), 157–173.

    Article  MATH  MathSciNet  Google Scholar 

  • Wu, Y., & Duan, Z. (2015). Visualization analysis of author collaborations in schizophrenia research. BMC Psychiatry, 15(1), 27.

    Article  MathSciNet  Google Scholar 

  • Wu, Z., Xu, J., & Xu, Z. S. (2015). A multiple attribute group decision making framework for the evaluation of lean practices at logistics distribution centers. Annals of Operations Research, 1–23.

  • Wuehrer, G. A., & Smejkal, A. E. (2013). The knowledge domain of the academy of international business studies (AIB) conferences: A longitudinal scientometric perspective for the years 2006–2011. Scientometrics, 95(2), 541–561.

    Article  Google Scholar 

  • Xu, Z. S. (2010). Choquet integrals of weighted intuitionistic fuzzy information. Information Sciences, 180(5), 726–736.

    Article  MATH  MathSciNet  Google Scholar 

  • Xu, Z. S. (2015). Uncertain multi-attribute decision making: Methods and applications. New York: Springer.

    Book  Google Scholar 

  • Xu, Z. S., & Yager, R. R. (2006). Some geometric aggregation operators based on intuitionistic fuzzy sets. International Journal of General Systems, 35(4), 417–433.

    Article  MATH  MathSciNet  Google Scholar 

  • Xu, Z. S., & Yager, R. R. (2008). Dynamic intuitionistic fuzzy multi-attribute decision making. International Journal of Approximate Reasoning, 48(1), 246–262.

    Article  MATH  MathSciNet  Google Scholar 

  • Xu, Z. S., & Yager, R. R. (2009). Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group. Fuzzy Optimization and Decision Making, 8(2), 123–139.

    Article  MATH  MathSciNet  Google Scholar 

  • Xu, Z., & Yager, R. R. (2010). Power-geometric operators and their use in group decision making. IEEE Transactions on Fuzzy Systems, 18(1), 94–105.

    Article  Google Scholar 

  • Xu, Z. S., & Yager, R. R. (2011). Intuitionistic fuzzy Bonferroni means. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics, 41(2), 568–578.

    Article  Google Scholar 

  • Yager, R. R. (1988). On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Transactions on Systems, Man and Cybernetics, 18(1), 183–190.

    Article  MATH  MathSciNet  Google Scholar 

  • Yager, R. R. (1993). Families of OWA operators. Fuzzy Sets and Systems, 59(2), 125–148.

    Article  MATH  MathSciNet  Google Scholar 

  • Yager, R. R. (1994). Aggregation operators and fuzzy systems modeling. Fuzzy Sets and Systems, 67(2), 129–145.

    Article  MATH  MathSciNet  Google Scholar 

  • Yager, R. R. (1996). Quantifier guided aggregation using OWA operators. International Journal of Intelligent Systems, 11(1), 49–73.

    Article  Google Scholar 

  • Yager, R. R. (2004). Generalized OWA aggregation operators. Fuzzy Optimization and Decision Making, 3(1), 93–107.

    Article  MATH  MathSciNet  Google Scholar 

  • Yager, R. R., & Filev, D. P. (1999). Induced ordered weighted averaging operators. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics, 29(2), 141–150.

    Article  Google Scholar 

  • Yager, R. R., & Kacprzyk, J. (2012). The ordered weighted averaging operators: Theory and applications. New York: Springer.

    Google Scholar 

  • Yager, R. R., & Xu, Z. S. (2006). The continuous ordered weighted geometric operator and its application to decision making. Fuzzy Sets and Systems, 157(10), 1393–1402.

    Article  MATH  MathSciNet  Google Scholar 

  • Yoshikane, F. (2013). Multiple regression analysis of a patent’s citation frequency and quantitative characteristics: The case of Japanese patents. Scientometrics, 96(1), 365–379.

    Article  Google Scholar 

  • Yu, D. J. (2012). Group decision making based on generalized intuitionistic fuzzy prioritized geometric operator. International Journal of Intelligent Systems, 27(7), 635–661.

    Article  Google Scholar 

  • Yu, D. J. (2013). Intuitionistic fuzzy geometric Heronian mean aggregation operators. Applied Soft Computing, 13(2), 1235–1246.

    Article  Google Scholar 

  • Yu, D. J. (2014). Intuitionistic fuzzy information aggregation under confidence levels. Applied Soft Computing, 19, 147–160.

    Article  Google Scholar 

  • Yu, D. J. (2015a). Group decision making under interval-valued multiplicative intuitionistic fuzzy environment based on Archimedean t-Conorm and -Norm. International Journal of Intelligent Systems, 30(5), 590–616.

    Article  Google Scholar 

  • Yu, D. J. (2015b). Intuitionistic fuzzy theory based typhoon disaster evaluation in Zhejiang Province, China: A comparative perspective. Natural Hazards, 75(3), 2559–2576.

    Article  Google Scholar 

  • Yu, D. J., Zhang, W. Y., & Xu, Y. J. (2013). Group decision making under hesitant fuzzy environment with application to personnel evaluation. Knowledge-Based Systems, 52, 1–10.

    Article  Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.

    Article  MATH  MathSciNet  Google Scholar 

  • Zadeh, L. A. (1983). A computational approach to fuzzy quantifiers in natural languages. Computers and Mathematics with Applications, 9(1), 149–184.

    Article  MATH  MathSciNet  Google Scholar 

  • Zimmermann, H. J., & Zysno, P. (1980). Latent connectives in human decision making. Fuzzy Sets and Systems, 4(1), 37–51.

    Article  MATH  Google Scholar 

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Acknowledgments

This work has been supported by China National Natural Science Foundation (No. 71301142), Zhejiang Science and Technology Plan of China (2015C33024), Zhejiang Provincial Natural Science Foundation of China (No. LQ13G010004), Project Funded by China Postdoctoral Science Foundation (No. 2014M550353), Projects of the Zhejiang Province planning of educational research (No. 14YJC630090) and the National Education Information Technology Research (No. 146242069).

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  1. School of Information, Zhejiang University of Finance and Economics, Hangzhou, 310018, Zhejiang, China

    Dejian Yu

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Yu, D. A scientometrics review on aggregation operator research. Scientometrics 105, 115–133 (2015). https://doi.org/10.1007/s11192-015-1695-2

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