Abstract
Policy-oriented object ranking is of great importance in the field of object recommendation and target retrieval, such as e-commerce recommendation system, financial services and selecting hosts of some large-scale sports events. However, the solution of such problem is often accompanied by the processing of massive high-dimensional data. The typical methods may lead to the phenomenon of over-reliance on historical data as well as ignoring the interactions among indicators. This also causes the ranking results to lose part of the timeliness and sensitivity. We designed Entropy-weighted Synthetic Model (ESM) in order to optimize the defects above. We focus on the case of Olympic Host Country or Region Selection to demonstrate the superiority of our method. We first fulfill calculation of synthetic property weights and differential data of each attribute based on time series of the selected synthetic group. Then we evaluate the weight of each indicator, obtain the comprehensive scores and generate the ranking results of the target countries or regions. Last, we implement Placebo Test to eliminate the effects of Synthetic Control Method (SCM) and validate the robustness of the model with the support of Hypothesis Test. From the perspective of comparing with the results of Difference-in-Difference Model (DID) and Propensity Score Matching (PSM), ESM shows better adaptability and predictability and provide conclusion consistent with professional perspective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kang, Y.: Long-term impact of a mega-event on international tourism to the host country or region a conceptual model and the case of the 1988 Seoul Olympics. J. Int. Consum. Market. 6(3), 205–226 (1994)
Mueller, M.: The mega-event syndrome: why so much goes wrong in mega-even planning and what to do about it. J. Am. Plann. Assoc. 81(1), 6–17 (2015)
Baade, R., Baumann, R., Matheson, V.: Assessing the economic impact of college football games on local economies. J. Sports Econ. 9(6), 628–643 (2008)
Zeng, J., Zhou, J.: Variable selection for high-dimensional data model a survey. J. Appl. Stat. Manag. 36(4), 678–692 (2017). (In Chinese)
Bert, R.: World economy. Econ. Outlook 46(1), 32–34 (2022)
Xia, X., Huang, T., Zhang, S.: The impact of intellectual property rights city policy on firm green innovation a quasi-natural experiment based on a staggered did model. Systems 11(209), 209 (2023)
He, T., Chen, W.: Evaluation of sustainable development policy of Sichuan citrus industry in China based on DEA–Malmquist index and did model. Sustainability 15(4260), 4260 (2023)
Wang, X., Hu, S.: Does university-industry collaboration improve the technological innovation performance of manufacturing firms? An empirical study based on propensity score matching method. Technol. Econ. 41(4), 30–43 (2022). (In Chinese)
Liu, J., Zhang, G., Li, C.: Human capital, social capital, and farmers’ credit availability in China based on the analysis of the ordered probit and PSM models. Sustainability 12(4), 1583 (2020)
Abadie, A., Gardeazabal, J.: The economic costs of conflict a case study of the Basque country. Am. Econ. Rev. 93(1), 113–132 (2003)
Abadie, A., Diamond, A., Hainmueller, A.: Synthetic control methods for comparative case studies estimating the effect of California’s tobacco control program. J. Am. Stat. Assoc. 105(490), 493–505 (2010)
Jin, D., Yang, M., Qin, Z., Peng, J., Ying, S.: A weighting method for feature dimension by semi-supervised learning with entropy. IEEE Trans. Neural Netw. Learn. Syst. 34(3), 1218–1227 (2023)
Fullman, N.: Measuring performance on the healthcare access and quality index for 195 countries and territories and selected subnational locations a systematic analysis from the global burden of disease study 2016. The Lancet 391(10136), 2236–2271 (2018)
Check, A., Nolan, A., Schipper, T.: Forecasting GDP growth using disaggregated GDP revisions. Econ. Bull. 39(4), 2580–2588 (2019)
Abadie, A., Diamond, A., Hainmueller, J.: Comparative politics and the synthetic control method. Am. J. Polit. Sci. 59(2), 495–510 (2015)
Chen, C., Zhang, H.: Evaluation of green development level of Mianyang agriculture, based on the entropy weight method. Sustainability 15(7589), 7589 (2023)
Wang, Y., Gao, S., Li, W., Jiang, T., Yu, S.: Research and application of personalized recommendation based on knowledge graph. In: Xing, C., Fu, X., Zhang, Y., Zhang, G., Borjigin, C. (eds.) Web Information Systems and Applications: 18th International Conference, WISA 2021, Kaifeng, China, September 24–26, 2021, Proceedings, pp. 383–390. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-87571-8_33
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Cui, H., He, J., Zeng, W. (2023). Policy-Oriented Object Ranking with High-Dimensional Data: A Case Study of Olympic Host Country or Region Selection. In: Yuan, L., Yang, S., Li, R., Kanoulas, E., Zhao, X. (eds) Web Information Systems and Applications. WISA 2023. Lecture Notes in Computer Science, vol 14094. Springer, Singapore. https://doi.org/10.1007/978-981-99-6222-8_19
Download citation
DOI: https://doi.org/10.1007/978-981-99-6222-8_19
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6221-1
Online ISBN: 978-981-99-6222-8
eBook Packages: Computer ScienceComputer Science (R0)
