{"title":"基于关联挖掘的大数据下企业技术创新智能决策方法","authors":"Qianqian Zhang, Guining Geng, Qun Tu","doi":"10.15837/ijccc.2023.2.5241","DOIUrl":null,"url":null,"abstract":"\nTechnological innovation is vital for the survival and development of enterprises. In the era of intelligent information interconnection and knowledge-driven economy, there is a growing interest in how to manage high-volume data, unlock its potential value, and provide intelligent analysis and decision-making support for enterprise’s technological innovation. This paper proposes an improved knowledge association analysis method based on the semantic concept model. This approach enables the discovery of potential correlations and interaction modes between the influencing factors of enterprise’s technological innovation, and provides a useful reference for decision-making by combining the analysis with the enterprise’s own situation.\n","PeriodicalId":179619,"journal":{"name":"Int. J. Comput. Commun. Control","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Association mining-based method for enterprise's technological innovation intelligent decision making under big data\",\"authors\":\"Qianqian Zhang, Guining Geng, Qun Tu\",\"doi\":\"10.15837/ijccc.2023.2.5241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nTechnological innovation is vital for the survival and development of enterprises. In the era of intelligent information interconnection and knowledge-driven economy, there is a growing interest in how to manage high-volume data, unlock its potential value, and provide intelligent analysis and decision-making support for enterprise’s technological innovation. This paper proposes an improved knowledge association analysis method based on the semantic concept model. This approach enables the discovery of potential correlations and interaction modes between the influencing factors of enterprise’s technological innovation, and provides a useful reference for decision-making by combining the analysis with the enterprise’s own situation.\\n\",\"PeriodicalId\":179619,\"journal\":{\"name\":\"Int. J. Comput. Commun. Control\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Commun. Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15837/ijccc.2023.2.5241\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Commun. Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15837/ijccc.2023.2.5241","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Association mining-based method for enterprise's technological innovation intelligent decision making under big data
Technological innovation is vital for the survival and development of enterprises. In the era of intelligent information interconnection and knowledge-driven economy, there is a growing interest in how to manage high-volume data, unlock its potential value, and provide intelligent analysis and decision-making support for enterprise’s technological innovation. This paper proposes an improved knowledge association analysis method based on the semantic concept model. This approach enables the discovery of potential correlations and interaction modes between the influencing factors of enterprise’s technological innovation, and provides a useful reference for decision-making by combining the analysis with the enterprise’s own situation.