信息资源管理学报 ›› 2020, Vol. 10 ›› Issue (3): 18-26.doi: 10.13365/j.jirm.2020.03.018

• 研究论文 • 上一篇    下一篇

大数据时代知识融合的支撑理论架构

于梦月 申 静   

  1. 北京大学信息管理系,北京,100871
  • 出版日期:2020-05-26 发布日期:2020-05-26
  • 作者简介:于梦月,博士研究生,研究方向为知识管理;申静(通讯作者),教授,博士生导师,研究方向为知识管理与服务创新,Email:jshen@pku.edu.cn。
  • 基金资助:
    本文系2015年度国家社会科学基金重大项目“大数据时代知识融合的体系架构、实现模式及实证研究”(15ZDB129)的研究成果之一。

Supporting Theory Framework for Knowledge Fusion in the Era of Big Data

Yu Mengyue  Shen Jing   

  1. Department of Information Management, Peking University, Beijing, 100871
  • Online:2020-05-26 Published:2020-05-26

摘要: 设计大数据时代知识融合的支撑理论架构可以有效指导知识融合的实现路径和服务模式。基于知识融合的三阶段论,通过梳理和剖析知识融合前、融合过程和融合后的相关支撑理论,设计大数据时代知识融合的支撑理论架构。该架构为大数据时代的知识融合全过程提供了相关理论支撑,由三个层次、三个阶段、十五个理论组成,包括知识融合前融合的原因与融合对象的选取,知识融合过程中知识的转换、表示、计算与融合算法的实施,知识融合后知识的可视化与效果评价等相关理论。

关键词: 大数据时代, 知识融合, 融合全过程, 三阶段论, 理论架构

Abstract: The supporting theory of knowledge fusion in the era of big data can effectively guide the implementing paths and service patterns of knowledge fusion. Based on the three-stage theory of knowledge fusion, the supporting theoretical framework of knowledge fusion in the era of big data is designed by combing and analyzing the relevant support theory before, during and after the fusion of knowledge. This architecture provides relevant theoretical support for the whole process of knowledge fusion in the era of big data. It consists of three levels, three stages, and fifteen theories, including various related theories such as the reasons for fusion and the selection of fusion objects before knowledge fusion, the transformation, representation, calculation and fusion of knowledge in the process, the visualization and effect evaluation of knowledge after knowledge fusion.

Key words: Big data era, Knowledge fusion, Fusion process, Three-stage theory, Theoretical framework

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