{"title":"Evaluation index system and methodology for actively responding to ageing population","authors":"Si-bo Yang, Ai-hua Li, Guijun Li","doi":"10.1145/3498851.3499005","DOIUrl":null,"url":null,"abstract":"Ageing population is a challenge faced by the global community. According to international standards for measuring ageing society, China has entered the ageing society since 2000. Currently, actively responding to ageing population has become one of China's national strategies. Increasingly, actively responding to ageing population is gaining greater attention, but there lacks a comprehensive evaluation index system and model. Based on China's real situations, we scientifically and comprehensively construct an evaluation index system for actively responding to ageing population, using source statistical surveys, social tracking surveys and other multi-source heterogeneous data. Best-Worst Method (BWM) and K-means clustering algorithm are used here to evaluate ageing population measuring nationwide with a scientific and comprehensive index system. This paper also analyses and evaluates the measurement taken by 31 districts in China, thus carrying both theoretical and practical implications. With the emergence of big data for government administration, the rigor of the evaluation outcome will enhance.","PeriodicalId":89230,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3498851.3499005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Ageing population is a challenge faced by the global community. According to international standards for measuring ageing society, China has entered the ageing society since 2000. Currently, actively responding to ageing population has become one of China's national strategies. Increasingly, actively responding to ageing population is gaining greater attention, but there lacks a comprehensive evaluation index system and model. Based on China's real situations, we scientifically and comprehensively construct an evaluation index system for actively responding to ageing population, using source statistical surveys, social tracking surveys and other multi-source heterogeneous data. Best-Worst Method (BWM) and K-means clustering algorithm are used here to evaluate ageing population measuring nationwide with a scientific and comprehensive index system. This paper also analyses and evaluates the measurement taken by 31 districts in China, thus carrying both theoretical and practical implications. With the emergence of big data for government administration, the rigor of the evaluation outcome will enhance.