吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

从自然语言向SPARQL语言映射的歧义消解算法

董立岩1, 张高祥1, 孙博1, 郎一宁2   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012; 2. 北京理工大学 计算机学院, 北京 100081
  • 收稿日期:2015-12-18 出版日期:2016-05-26 发布日期:2016-05-20
  • 通讯作者: 张高祥 E-mail:85192510@qq.com

Ambiguity Resolution Algorithm for Mapping from Natural Language to SPARQL Languege

DONG Liyan1, ZHANG Gaoxiang1, SUN Bo1, LANG Yining2   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. School of Computer Science & Technology, Beijing Institute of Technology, Beijing 100081, China
  • Received:2015-12-18 Online:2016-05-26 Published:2016-05-20
  • Contact: ZHANG Gaoxiang E-mail:85192510@qq.com

摘要:

针对计算机各语言间的无岐义映射问题, 提出一种从自然语言向SPARQL语言映射过程中的歧义消解算法. 该算法基于自然语言的特征, 拟合知识丰富程度和文本相似度消解实体映射过程中的歧义性, 拟合语义权重度和文本相似度消解关系映射过程中的歧义性. 实验结果表明, 该算法效果较好.

关键词: 歧义消解, 文本相似度, 知识丰富程度, 语义权重度

Abstract:

Aiming at the problem of non ambiguity mapping between computer languages, we proposed an ambiguity resolution algorithm for mapping from natural language to SPARQL language. The algorithm was based on the characteristics of natural language, fitting quantity of facts and the text similarity to resolve ambiguity in the process of entity mapping, fitting the text similarity and the semanticsweight of relation to resolve the ambiguity in the process of relation mapping. Experimental results show that the algorithm is effective.

Key words: ambiguity resolution, text similarity, quantity of facts; , semanticsweight of relation

中图分类号: 

  • TP391