J4

• 计算机科学 • 上一篇    下一篇

一种基于扩展主题图的分布式知识融合

鲁慧民, 冯博琴, 赵英良, 郑庆华, 刘 均   

  1. 西安交通大学 电子与信息工程学院, 西安 710049
  • 收稿日期:2008-10-09 修回日期:1900-01-01 出版日期:2009-05-26 发布日期:2009-06-23
  • 通讯作者: 冯博琴

Distributed Knowledge Fusion Based on Extended Topic Maps

LU Huimin, FENG Boqin, ZHAO Yingliang, ZHENG Qinghua, LIU Jun   

  1. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
  • Received:2008-10-09 Revised:1900-01-01 Online:2009-05-26 Published:2009-06-23
  • Contact: FENG Boqin

摘要: 针对知识融合的效率问题, 扩展了传统主题图的组织结构, 并在此基础上构建一种基于扩展主题图的分布式知识融合体系结构, 提出一种基于全信息的主题图相似度算法, 设计了扩展主题图融合的规则和算法, 充分考虑了比较元素的涵义和所处语境, 提高了相似度算法的准确性, 实现了分布式环境下知识的有效融合.

关键词: 知识融合, 主题图, 知识元, 相似性算法

Abstract: Aiming at the efficiency of knowledge fusion, the authors extended the structure of conventionaltopicmaps. This new structure embodied the multilevel, multi-granularity and inherent relevant characteristics of knowledge. A new distributed knowledge fusion architecture based on extended topic maps was built up, and a novel algorithm of the similarity of topic maps based on comprehensive information was proposed by integrating syntactic similarity, semantic similarity and pragmatic similarity. It gave full consideration to the meaning and context of the compared elements so as to improve the accuracy of the similarity algorithm. The fusion rules and algorithm for extended topic maps were presented, implementing the effective knowledge fusion in distributed environment.

Key words: knowledge fusion, topic maps, knowledge element, similarity algorithm

中图分类号: 

  • TP391