Implementation of SPARQL Query Language Based on Graph Homomorphism

Second, the partial computation of results and facets entails a bias in the search, because the first results returned by SPARQL may not form a representative sample of all re-

Our main assumption, based on the size of the graph databases we want to query, is that main memory structures used in the implementation must be of size at most O(|V |) (i.e.,

Les larves effectuent leur développement dans les sols a des différentes profondeurs, Le développement larvaire se caractérise par 03 stades larvaires (INPV, 2015) :

In order to illustrate our language of abstract queries, and show its expressive power, we show below the table query T for the complex use case (C) of Section 2. ) T 0 is the

In this paper, based on SPARQL CONSTRUCT query, we present a new query form called SPARQL Analyze Query, which inte- grates graph analytics with graph querying.. SPARQL Analyze

While the IRIs returned by an edge label mapping are used as predicates of triples (see function e c,g in Definition 3.2 and, for instance, set G e in Example 3.2), a node label

For in- stance, the configuration (2, 1, {{OPTIONAL, FILTER}, {UNION}}, 10) makes QED construct a test suite containing 10 test cases with queries that contain both OPTIONAL and

Mapping SPARQL Query to temporal logic query based on NµSMV Model Checker to Query Semantic Graphs.. Mahdi Gueffaz, Sylvain Rampacek,