Abstract
With strong links to management, economics, business, engineering and other subjects, management science (MS) employs various scientific research-based principles, strategies, and analytical methods such as mathematical modeling and data analysis to make decisions and solve complex problems. In recent decades, there has been a significant increase in the scientific MS community, especially in the fields of data analysis and mining, decision support system, and computing science. This paper gives a brief introduction to the 13th ICMSEM proceedings Volume I, examines the reasons why data analysis and mining, decision support system, and computing science have become key foci in the past few years, and outlines the central research areas in the 13th ICMSEM proceedings Volume I in a brief literature review. Finally, CiteSpace is used to investigate the keywords to identify the frontier MS innovations. The ICMSEM continues to provide a valuable forum for academic exchange and communication to promote future management science and engineering management innovations.
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References
Ceri, S.: On the role of statistics in the era of big data: a computer science perspective. Stat. Probab. Lett. 136, 68–72 (2018)
Chaochao, Y., Li, W., et al.: Acupoint combinations used for treatment of alzheimer’s disease: a data mining analysis. J. Tradit. Chin. Med. 38(6), 943–952 (2018)
Chen, C., Ibekwesanjuan, F., Hou, J.: The structure and dynamics of co-citation clusters: a multiple-perspective co-citation analysis. J. Am. Soc. Inf. Sci. Technol. 61(7), 1386–1409 (2014)
Freitas, M.C., Xavier, A., Fragoso, R.: An integrated decision support system for the mediterranean forests. Land Use Policy 80, 298–308 (2019)
Keenan, P.B., Jankowski, P.: Spatial decision support systems: three decades on. Decis. Support Syst. 116, 64–76 (2019)
Merigó, J.M., Yang, J.B.: A bibliometric analysis of operations research and management science. Omega 73, 37–48 (2017)
Michell, D., Szabo, C., et al.: Towards a socio-ecological framework to address gender inequity in computer science. Comput. Educ. 126, 324–333 (2018)
Ng, D.K., Deng, J.: Contrasting grey system theory to probability and fuzzy. ACM Sigice B 20(3), 3–9 (1995)
Olson, R.: Percentage of bachelor’s degrees conferred to women, by major (1970–2012). Randal S Olson Retrieved Feb 22:2015 (2014)
Sato, Y., Izui, K., et al.: Data mining based on clustering and association rule analysis for knowledge discovery in multiobjective topology optimization. Expert. Syst. Appl. 119, 247–261 (2019)
Scherf, M., Epple, A., Werner, T.: The next generation of literature analysis: integration of genomic analysis into text mining. Brief. Bioinform. 6(3), 287–297 (2005)
Smelser, N.J., Baltes, P.B.: International Encyclopedia of the Social and Behavioral Sciences, vol. 11, Elsevier, Amsterdam (2001)
Taub, R., Armoni, M., et al.: The effect of computer science on physics learning in a computational science environment. Comput. Educ. 87, 10–23 (2015)
Wang, J., Yan, R., et al.: A historic review of management science research in china. Omega 36(6), 919–932 (2008)
Wang, R., Ji, W., et al.: Review on mining data from multiple data sources. Pattern Recognit. Lett. 109, 120–128 (2018)
Zarte, M., Pechmann, A., Nunes, I.L.: Decision support systems for sustainable manufacturing surrounding the product and production life cycle-a literature review. J. Clean. Prod. 219, 336–349 (2019)
Zemigala, M.: Tendencies in research on sustainable development in management sciences. J. Clean. Prod. (2019)
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The author gratefully acknowledges Tingting Liu and Jingqi Dai’s efforts on the paper collection and classification, Zongmin Li and Mengyuan Zhu’s efforts on data collation and analysis, and Rongwei Sun and Yawen Deng’s efforts on the chart drawing.
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Xu, J. (2020). Advancement of Data Analysis and Mining, Decision Support System, and Computing Science Based on the Thirteenth ICMSEM Proceedings. In: Xu, J., Ahmed, S., Cooke, F., Duca, G. (eds) Proceedings of the Thirteenth International Conference on Management Science and Engineering Management. ICMSEM 2019. Advances in Intelligent Systems and Computing, vol 1001. Springer, Cham. https://doi.org/10.1007/978-3-030-21248-3_1
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DOI: https://doi.org/10.1007/978-3-030-21248-3_1
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