Application research of data envelopment analysis and multimedia information fusion algorithm in public performance management

  • Ruopu ChenEmail author


Under the increasingly complex social and economic environment, it is particularly important to conduct scientific performance evaluation and analysis. As an effective means of performance evaluation and management, multimedia data envelopment analysis has been widely used in various industries, and has produced numerous research results. At present, there are relatively few applications of multimedia data envelopment analysis in this area. The research of new multimedia data envelopment analysis model combined with modern data mining technology is scientific and innovative, and can provide certain performance for complex performance evaluation and analysis. In view of this, the paper firstly studies the multimedia data envelopment analysis model by combining fuzzy c-means clustering, principal component analysis and multimedia data envelopment analysis, and establishes the multimedia data envelopment optimization selection model and PCA-DEA. The model is mixed and the solution algorithm is given. Then, using the collected local unit data, the multimedia data envelope index data is constructed, and the established model is used to analyze the multimedia data envelope. The research results show that the established model combines the characteristics of data mining technology and multimedia data envelopment analysis method to meet certain complex performance evaluation and analysis requirements, and can provide certain data support for local public performance management.


Multimedia data Data envelopment analysis Multimedia information Public performance management research 



  1. 1.
    Amirteimoori A, Kordrostami S (2012) A distance-based measure of super efficiency in data envelopment analysis: an application to gas companies[J]. J Glob Optim 54(1):117–128MathSciNetCrossRefGoogle Scholar
  2. 2.
    Banker RD, Chang H, Feroz EH (2014) Performance measurement in nonprofit governance: an empirical study of the Minnesota independent school districts[J]. Ann Oper Res 221(1):47–71MathSciNetCrossRefGoogle Scholar
  3. 3.
    Debnath RM, Sebastian VJ (2014) Efficiency in the Indian iron and steel industry - an application of data envelopment analysis[J]. Journal of Advances in Management Research 11(1):4–19CrossRefGoogle Scholar
  4. 4.
    El-Banna M (2015) A novel approach for classifying imbalance welding data: Mahalanobis genetic algorithm (MGA)[J]. Int J Adv Manuf Technol 77(1–4):407–425CrossRefGoogle Scholar
  5. 5.
    Geng R, Bose I et al (2015) Prediction of financial distress: an empirical study of listed Chinese companies using data mining[J]. Eur J Oper Res 241(1):236–247CrossRefGoogle Scholar
  6. 6.
    Gulen E, Yilmaz T, Yazici A (2012) Multimodal information fusion for semantic video analysis[J]. International Journal of Multimedia Data Engineering & Management 3(4):52–74CrossRefGoogle Scholar
  7. 7.
    Han Y, Geng Z, Liu Q (2014) Energy efficiency evaluation based on data envelopment analysis integrated analytic hierarchy process in ethylene production[J]. Chin J Chem Eng 22(11–12):1279–1284CrossRefGoogle Scholar
  8. 8.
    Kao C (2014) Efficiency decomposition for general multi-stage systems in data envelopment analysis[J]. Eur J Oper Res 232(1):117–124MathSciNetCrossRefGoogle Scholar
  9. 9.
    Pahlavan R, Omid M, Akram A (2018) Application of data envelopment analysis for performance assessment and energy efficiency improvement opportunities in greenhouses cucumber production[J]. J Agric Sci Technol 14(3):1465–1475Google Scholar
  10. 10.
    Rahimi B, Yusefzadeh H, Khalesi N et al (2012) Analysis of the efficiency and optimal consumption of resources in selected hospitals in Urmia Province through data envelopment analysis[J]. Cem Concr Res 30(12):1955–1960Google Scholar
  11. 11.
    Rezaee MJ, Moini A, Asgari HA (2012) Unified performance evaluation of health centers with integrated model of data envelopment analysis and bargaining game[J]. J Med Syst 36(6):3805–3815CrossRefGoogle Scholar
  12. 12.
    Sengupta J, Sahoo B (2012) Efficiency models in data envelopment analysis: techniques of evaluation of productivity of firms in a growing economy[J]. Social Science Electronic Publishing 25(5):548–554Google Scholar
  13. 13.
    Shirouyehzad H (2012) Performance evaluation of hotels by data envelopment analysis based on customers’ perception and gap analysis[J]. International Journal of Services & Operations Management 12(4):447–467CrossRefGoogle Scholar
  14. 14.
    Tavassoli M, Faramarzi GR, Saen RF (2014) A joint measurement of efficiency and effectiveness using network data envelopment analysis approach in the presence of shared input[J]. Opsearch 52(3):1–15MathSciNetzbMATHGoogle Scholar
  15. 15.
    Tosun O (2012) Using data envelopment analysis-neural network model to evaluate hospital efficiency[J]. International Journal of Productivity & Quality Management 9(2):245–257CrossRefGoogle Scholar
  16. 16.
    Wen M, Qin Z, Kang R et al (2015) Sensitivity and stability analysis of the additive model in uncertain data envelopment analysis[J]. Soft Computing - A Fusion of Foundations, Methodologies and Applications 19(7):1987–1996Google Scholar
  17. 17.
    Wood DR (2012) The effect on gastric secretion of different rates of histamine infusion and of ‘Neoantergan’[J]. Br J Pharmacol 3(3):231–236Google Scholar
  18. 18.
    Yadav VK, Kumar N, Ghosh S et al (2014) Indian thermal power plant challenges and remedies via application of modified data envelopment analysis.[J]. Int Trans Oper Res 21(6):955–977MathSciNetCrossRefGoogle Scholar
  19. 19.
    Yeboon Y, Hirotaka N (2012) Generation of Pareto optimal solutions using expected improvement and generalized data envelopment analysis[J]. Transactions of the Institute of Systems Control & Information Engineers 25(8):189–195CrossRefGoogle Scholar
  20. 20.
    Yuan M, Sheng H (2017) Research on the fusion method of spatial data and multimedia information of multimedia sensor networks in cloud computing environment[J]. Multimed Tools Appl 76(16):17037–17054CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Chongqing Industry Polytechnic CollegeChongqingChina

Personalised recommendations