基于大数据挖掘的行业知识服务研究  

Research on Industry Knowledge Service Based on Big Data Mining

作　　者：胡潜[1] 李梦婷 黄家娥 Hu Qian

机构地区：[1]华中师范大学信息管理学院,湖北武汉430079

出　　处：《情报理论与实践》2021年第8期90-94,共5页Information Studies:Theory & Application

基　　金：国家社会科学基金项目“‘互联网+’背景下面向产业链的行业信息服务融合研究”的成果,项目编号:16BTQ063。

摘　　要：[目的/意义]近年来大数据技术和产业快速发展,将技术与行业内容知识相结合对行业服务创新具有重大意义。[方法/过程]在调研学术研究与实践进展基础上,构建了基于大数据挖掘的行业知识服务层次模型,并立足行业知识服务现状对基于大数据挖掘的行业知识服务发展策略进行探讨。[结果/结论]基于大数据挖掘可以从专家发现、创新支持、市场信息和行业管理支持方面深化行业知识服务,其实现模型可以分为基础设施层、数据资源层、数据治理层、数据挖掘层、服务功能层5个层次。为发展基于大数据挖掘的行业知识服务,需要重点推进行业大数据建设的跨组织协同机制构建、跨语言行业大数据资源建设与挖掘以及开放化的行业知识服务平台构建。[Purpose/significance]In recent years,big data technology and industry have developed rapidly.In this context,how to make good use of technology dividend to innovate industry knowledge service is of great significance.[Method/process]Based on the investigation of academic research and practice progress,this paper constructs a hierarchical model of industry knowledge service based on big data mining,and the development strategy of industry knowledge services based on big data mining is discussed based on the current situation of industry knowledge services.[Result/conclusion]Based on big data mining,industry knowledge services can be deepened from expert discovery,innovation support,market information and industry management support.The implementation model can be divided into five levels:infrastructure layer,data resource layer,data governance layer,data mining layer,and service function layer.In order to develop the industry knowledge service based on big data mining,it is necessary to focus on the construction of cross-organizational synergetic mechanism,the construction and mining of cross-language industry big data resources,and the construction of an open industry knowledge service platform.

关 键 词：行业大数据 大数据挖掘 行业知识服务 发展机制 

分 类 号：G252[文化科学—图书馆学]