数据驱动的专家知识资源建模方法与原型系统开发研究

DATA-DRIVEN EXPERT KNOWLEDGE RESOURCE MODELING METHOD AND PROTOTYPE SYSTEM DEVELOPMENT

专家知识资源是企业进行业务执行时,最重要的关键资源。快速高效组织专家资源的能力将是决定企业竞争力的重要因素。然而目前企业在知识管理方面的欠缺及专家资源信息获取能力的不足造成很多企业在组织专家资源方面的困扰。缺乏科学合理的专家资源家建模方法与技术是其中的关键。大数据的快速发展及网络开放数据的增加,形成数据驱动方法,构建专家知识资源模型。基于该构思,提出一种数据驱动的,基于映射规则的专家知识资源建模方法。利用多源数据融合与抽取技术,构造比较全面的专家知识资源描述模型,为企业配置、业务绩效提升提供方法和技术支持。该研究对提升企业的知识利用能力、提升企业创新水平有重要价值。

Expert knowledge resources are the most important key resources for business execution.The ability to organize expert resources quickly and efficiently is an important factor in determining a company s competitiveness.However, the current lack of knowledge management and access to expert resource information has caused many companies to be confused about the organization of expert resources.The key is the lack of scientific and reasonable methods and techniques for expert resource modeling.The rapid development of big data and the increase of open data in the Internet, lead to the construction of an expert knowledge resource model with a data-driven manner.Based on this conception, this paper proposed a data-driven modeling method for expert knowledge resources based on mapping rules.It used a multi-source data fusion and extraction technology to construct a more comprehensive model of describing expert knowledge resource, which provided supports of techniques and methods for enterprise configuration and business performance improvement.The research is of great value to enhance the ability of enterprises to use knowledge and improve their innovation level.