摘要
RDF模糊查询是实现语义Web智能检索的重要组成部分,利用Zadeh的Ⅱ型模糊集合理论、α-截集及语言变量概念,提出了支持用户偏好的RDF模糊查询方法,其扩展了SPARQL语言来实现模糊及偏好表达,构造了有序语言值子域表来实现模糊值到相应子域的映射,以确定隶属度区间。利用去模糊化规则,将扩展的查询转换为标准SPARQL,利用现有的SPARQL查询引擎实现模糊查询操作。为验证提出的方法,开发了fp-SPARQL实验系统。实验结果表明,该方法提高了RDF模糊查询效率,增强了用户对查询结果的满意度。
RDF fuzzy retrieval is an important module for realizing intelligent retrieval in Semantic Web. In this paper, Zadeh＇s type-II fuzzy set theory,as well as the concepts of α-cut set and linguistic variable was adopted to put forward the RDF fuzzy retrieval mechanism supporting user preference, which extends SPARQL to express fuzzy and preference conditions. Moreover,ordered sub-domain table of linguistic values was constructed to realize the projection from the fuzzy values to relayed sub-domains in the table, so as to figure out the interval of membership. On this basis, extended queries were then converted into standard SPARQL queries with a set of defuzzification rules, so as to achieve fuzzy re- trieval operations. In order to test the ideology proposed in this paper, the fp-SPARQL retrieval system was developed. According to the result of this experiment, the method improves the performance of RDF fuzzy retrieval, and corres- pondingly, users＇ satisfaction rate on the retrieval results is also enhanced.
出处
《计算机科学》
CSCD
北大核心
2013年第8期176-180,共5页
Computer Science
基金
国家自然科学基金项目(61073139)资助
