摘要： ￢RDF在RDF中引入经典否定和推理，以增强RDF的表达和推理能力，但经典否定会使程序出现不一致情况，导致程序无解。为此，提出一种基于加权回答集程序的加权￢RDF(￢WRDF)推理方法。借鉴加权回答集思想，通过加权回答集程序对￢WRDF进行推理，给出其应用实例。实例应用结果表明，该方法使得程序在不一致的情况下，仍然可以得到最接近用户需求的解。

关键词: 语义网, 经典否定, 加权￢RDF, 加权回答集, 权值

Abstract: ￢RDF introduces the classical negation of answer set programming into RDF, which improves the capacities of the expression and reasoning of semantic Web. However, due to the introduce of classical negation, sometimes there is inconsistence when reasoning ￢RDF with answer set programming, which causes the program to no solution. This paper learns from the ideas of weighted answer sets, and forms Weighted ￢RDF(￢WRDF). It discovers implicit facts through weighted answer sets. Example proves that the reasoning method provides the best solution to the users’ needs when the program is inconsistent.

Key words: semantic Web, classical negation, Weighted ￢RDF(￢WRDF), weighted answer set, weight

中图分类号: 

• TP311.12