Skip to main content

Advancement of Data Analysis and Mining, Decision Support System, and Computing Science Based on the Thirteenth ICMSEM Proceedings

  • Conference paper
  • First Online:
  • 932 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1001))

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.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Ceri, S.: On the role of statistics in the era of big data: a computer science perspective. Stat. Probab. Lett. 136, 68–72 (2018)

    Article  MathSciNet  Google Scholar 

  2. 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)

    Article  Google Scholar 

  3. 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)

    Article  Google Scholar 

  4. Freitas, M.C., Xavier, A., Fragoso, R.: An integrated decision support system for the mediterranean forests. Land Use Policy 80, 298–308 (2019)

    Article  Google Scholar 

  5. Keenan, P.B., Jankowski, P.: Spatial decision support systems: three decades on. Decis. Support Syst. 116, 64–76 (2019)

    Article  Google Scholar 

  6. Merigó, J.M., Yang, J.B.: A bibliometric analysis of operations research and management science. Omega 73, 37–48 (2017)

    Article  Google Scholar 

  7. Michell, D., Szabo, C., et al.: Towards a socio-ecological framework to address gender inequity in computer science. Comput. Educ. 126, 324–333 (2018)

    Article  Google Scholar 

  8. Ng, D.K., Deng, J.: Contrasting grey system theory to probability and fuzzy. ACM Sigice B 20(3), 3–9 (1995)

    Article  Google Scholar 

  9. Olson, R.: Percentage of bachelor’s degrees conferred to women, by major (1970–2012). Randal S Olson Retrieved Feb 22:2015 (2014)

    Google Scholar 

  10. 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)

    Article  Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. Smelser, N.J., Baltes, P.B.: International Encyclopedia of the Social and Behavioral Sciences, vol. 11, Elsevier, Amsterdam (2001)

    Google Scholar 

  13. 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)

    Article  Google Scholar 

  14. Wang, J., Yan, R., et al.: A historic review of management science research in china. Omega 36(6), 919–932 (2008)

    Article  Google Scholar 

  15. Wang, R., Ji, W., et al.: Review on mining data from multiple data sources. Pattern Recognit. Lett. 109, 120–128 (2018)

    Article  Google Scholar 

  16. 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)

    Article  Google Scholar 

  17. Zemigala, M.: Tendencies in research on sustainable development in management sciences. J. Clean. Prod. (2019)

    Google Scholar 

Download references

Acknowledgement

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiuping Xu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

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

Download citation

Publish with us

Policies and ethics