A Query Approximating Approach Over RDF Graphs

A Query Approximating Approach Over RDF Graphs

Ala Djeddai, Hassina Seridi-Bouchelaghem, Med Tarek Khadir
DOI: 10.4018/ijitwe.2013100105
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Abstract

Regardless of the knowledge structure lack about Resource Description Framework (RDF) data, difficulties, principally, occur in specifying and answering queries. Approximate querying is the solution to find relevant information by getting a set of sub structures (e.g. sub graphs) matching the query. Approaches based on the structure and others based on semantic, marginalized the common meaning between concepts in its computing. In this paper in order to improve the approximation by introducing the meaning similarity between components in the query and RDF components is proposed, getting better need satisfaction. The meaning similarity measure can be calculated using WordNet and used in all steps of the query answering process. In addition, other important properties in the approximation level calculation between query paths and RDF paths are considered; besides indexing and optimizations strategies are performed. Answers are a set of sub graphs ranked in decreasing order on its matching degree. Experiments are conducted within real RDF dataset.
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Many approaches have been proposed to approximate querying over RDF data. The authors in De Virgilio, Maccioni, and Torlone (2012, 2013) compute the approximate solutions (sub graphs) using path alignment trying to find similar RDF paths in the query paths using a similarity measures based on edit distance operations of edges and nodes (deletion, insertion, etc). In (Zhang, Song, He, Shi, & Dong, 2012) a similarity oriented RDF graph matching is proposed and can be used in approximate querying (one of the two graphs may be a query graph), based on computing similarities between triples of the two RDF graphs. In Carroll (2002) an RDF matching work based on graph isomorphism is proposed that can be used in approximate querying i.e. the source graph is a query. An interesting work is presented in Hurtado, Poulovassilis, and Wood (2009) which is an automata based approach considering the edit distance operations and creating an approximate automata. The RDF graph explorations are performed with respect to that automata to finding the node answers.

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