Approach for Querying RDF with Fuzzy Conditions and User Preferences
Jingwei Cheng · 2013
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 retrieval 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.