基于多源知识融合的企业知识管理方法

发布时间：2018-03-04 05:00

本文选题：知识管理　切入点：网络行为建模　出处：《科研管理》2015年08期 　论文类型：期刊论文

【摘要】：作为知识经济时代出现的新兴管理方法,企业知识管理的一个重要的研究课题,是对组织成员和人力资源的知识管理。传统的知识管理方法基于封闭的企业管理历史数据,不能深入地挖掘企业管理知识。本文拟从网络数据的行为建模和多源数据融合的角度,探索新的企业知识管理方法。以企业知识管理为研究目标,以石化企业员工为研究对象,以自然语言分析和处理为模式表示方法,以统计机器学习为知识分析工具,重点研究如何通过网络行为建模和多源数据融合,从而更全方位地对企业员工的性格、日常行为建立一套行之有效的分析机制,实现在开放网络时代的企业知识管理和绩效管理。在石化企业内部的知识管理实验性尝试表明,所提知识管理方法,能够更深入地对企业员工的行为进行分析和理解,能够更有效地将员工行为和企业人力资源中的若干关键指标建立相关性模型,从而为企业的知识管理和决策人员提供强有力的技术支持。
[Abstract]:As a new management method in the era of knowledge economy, the knowledge management of enterprise is an important research subject, which is the knowledge management of organization members and human resources. The traditional knowledge management method is based on the closed historical data of enterprise management. This paper attempts to explore a new method of enterprise knowledge management from the angle of behavior modeling of network data and multi-source data fusion. Taking natural language analysis and processing as the mode representation method and using statistical machine learning as knowledge analysis tool, this paper focuses on how to model network behavior and integrate multi-source data, so as to more comprehensively analyze the personality of enterprise employees. Daily behavior establishes a set of effective analysis mechanism to realize enterprise knowledge management and performance management in the open network era. The experimental experiment of knowledge management in petrochemical enterprises shows that the proposed knowledge management method, It can analyze and understand the behavior of employees more deeply, and establish the correlation model between employee behavior and several key indicators in enterprise human resources more effectively. In order to provide strong technical support for enterprise knowledge management and decision-making personnel.
【作者单位】：北京交通大学经济管理学院;北京化工大学;西安电子科技大学;
【分类号】：F272

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