{"title":"A Large Group Emergency Decision-Making Approach on HFLTS With Public Preference Data Mining","authors":"Mengke Zhao, Ji Guo, Xianhua Wu","doi":"10.4018/jgim.337610","DOIUrl":null,"url":null,"abstract":"Aiming at the emergency decision-making problem of major emergencies, this article proposes a large group emergency decision-making (LGEDM) approach with public opinions mining on hesitation fuzzy language term set (HFLTS). First, extract keywords that represent general preferences on events from the Weibo platform, classify keywords using the word similarity-based keyword clustering algorithm and identify decision attributes and their weights. Next, define the similarity measure and hesitation fuzzy entropy measure of HFLTS, quantify the decision risk of experts using the risk measurement model, and cluster all experts into several subgroups using the risk metric-based group clustering algorithm. Subsequently, assign clusters' weights on their risk value and size and obtain each cluster's preference matrix by the HIOWA operator. Finally, derive the ranking results of alternatives using the sorting process, and an example of “COVID-19” is presented to verify the rationality and effectiveness of the proposed method.","PeriodicalId":46306,"journal":{"name":"Journal of Global Information Management","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Global Information Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.4018/jgim.337610","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Aiming at the emergency decision-making problem of major emergencies, this article proposes a large group emergency decision-making (LGEDM) approach with public opinions mining on hesitation fuzzy language term set (HFLTS). First, extract keywords that represent general preferences on events from the Weibo platform, classify keywords using the word similarity-based keyword clustering algorithm and identify decision attributes and their weights. Next, define the similarity measure and hesitation fuzzy entropy measure of HFLTS, quantify the decision risk of experts using the risk measurement model, and cluster all experts into several subgroups using the risk metric-based group clustering algorithm. Subsequently, assign clusters' weights on their risk value and size and obtain each cluster's preference matrix by the HIOWA operator. Finally, derive the ranking results of alternatives using the sorting process, and an example of “COVID-19” is presented to verify the rationality and effectiveness of the proposed method.
期刊介绍:
Authors are encouraged to submit manuscripts that are consistent to the following submission themes: (a) Cross-National Studies. These need not be cross-culture per se. These studies lead to understanding of IT as it leaves one nation and is built/bought/used in another. Generally, these studies bring to light transferability issues and they challenge if practices in one nation transfer. (b) Cross-Cultural Studies. These need not be cross-nation. Cultures could be across regions that share a similar culture. They can also be within nations. These studies lead to understanding of IT as it leaves one culture and is built/bought/used in another. Generally, these studies bring to light transferability issues and they challenge if practices in one culture transfer.