{"title":"数据知识共同驱动的工程和管理创新。","authors":"Yingji Xia, Xiqun Michael Chen, Sudan Sun","doi":"10.1016/j.patter.2024.101114","DOIUrl":null,"url":null,"abstract":"<p><p>Modern intelligent engineering and management scenarios require advanced data utilization methodologies. Here, we propose and discuss data-knowledge co-driven innovations that could address emerging challenges, and we advocate for the adoption of interdisciplinary methodologies in numerous engineering and management applications.</p>","PeriodicalId":36242,"journal":{"name":"Patterns","volume":"5 12","pages":"101114"},"PeriodicalIF":7.4000,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11701839/pdf/","citationCount":"0","resultStr":"{\"title\":\"Data-knowledge co-driven innovations in engineering and management.\",\"authors\":\"Yingji Xia, Xiqun Michael Chen, Sudan Sun\",\"doi\":\"10.1016/j.patter.2024.101114\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Modern intelligent engineering and management scenarios require advanced data utilization methodologies. Here, we propose and discuss data-knowledge co-driven innovations that could address emerging challenges, and we advocate for the adoption of interdisciplinary methodologies in numerous engineering and management applications.</p>\",\"PeriodicalId\":36242,\"journal\":{\"name\":\"Patterns\",\"volume\":\"5 12\",\"pages\":\"101114\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11701839/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Patterns\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.patter.2024.101114\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Patterns","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.patter.2024.101114","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Data-knowledge co-driven innovations in engineering and management.
Modern intelligent engineering and management scenarios require advanced data utilization methodologies. Here, we propose and discuss data-knowledge co-driven innovations that could address emerging challenges, and we advocate for the adoption of interdisciplinary methodologies in numerous engineering and management applications.
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