计算机工程与应用 ›› 2014, Vol. 50 ›› Issue (7): 129-132.

• 数据库、数据挖掘、机器学习 • 上一篇    下一篇

基于知识库分割的多知识库整合方法

杨  龙1,2,张公让1,2,王  力1,2,魏炎炎1,2   

  1. 1.合肥工业大学 管理学院,合肥 230009
    2.合肥工业大学 过程优化与智能决策教育部重点实验室,合肥 230009
  • 出版日期:2014-04-01 发布日期:2014-04-25

Integration of multiple knowledge bases based on knowledge blocks

YANG Long1,2, ZHANG Gongrang1,2, WANG Li1,2, WEI Yanyan1,2   

  1. 1.School of Management, Hefei University of Technology, Hefei 230009, China
    2.Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei University of Technology, Hefei 230009, China
  • Online:2014-04-01 Published:2014-04-25

摘要: 知识库是集团企业云制造平台中知识服务的重要基础,知识库的质量直接决定着知识服务的质量。目前单一分散的知识库不能提供统一的知识资源全局视图,不利于知识资源的共享。多知识库整合技术已经成为该领域的研究热点之一。提出一种基于知识库分割的多知识库整合方法,采用基于蚁群聚类的分割策略,将知识库有效划分为知识块集。在知识块间利用语义概念映射生成知识块间映射图,从而实现多知识库整合。通过对算法的时间复杂度进行分析,表明该方法在时间复杂度方面要优于基于最小概念集的多知识库整合方法;实验结果也表明该方法在运行性能方面明显优于已有的方法。

关键词: 云制造, 多知识库整合, 蚁群聚类, 语义概念映射

Abstract: Knowledge base is an important foundation of knowledge services in the Group’s Enterprise Cloud manufacturing platform.As a result,the quality of the knowledge base directly determines the quality of knowledge services.Single dispersed knowledge base cannot provide a unified global view of the knowledge resources,which is not conducive to the sharing of knowledge resources.Multiple knowledge bases integration technology has become one of the focuses.An efficient integration of multiple knowledge bases method based on knowledge blocks is proposed,which divides a knowledge base into a set of blocks through an improved ant colony clustering algorithm.Then,the mapping between blocks is based on computing semantic similarity of candidate mapping entity pairs are selected from the block mapping result.Through the algorithm’s time complexity analysis,the time complexity is better than the method of integration based on the
minimum set of concepts knowledge base.The results also show that the operating performance of the method is obviously superior to existing methods.

Key words: cloud manufacturing, integration of multiple knowledge bases, ant colony clustering, semantic concept mapping