Answering SPARQL queries modulo RDF Schema with paths

SPARQL is the standard query language for RDF graphs. In its strict instantiation, it only offers querying according to the RDF semantics and would thus ignore the semantics of data expressed with respect to (RDF) schemas or (OWL) ontologies. Several extensions to SPARQL have been proposed to query RDF data modulo RDFS, i.e., interpreting the query with RDFS semantics and/or considering external ontologies. We introduce a general framework which allows for expressing query answering modulo a particular semantics in an homogeneous way. In this paper, we discuss extensions of SPARQL that use regular expressions to navigate RDF graphs and may be used to answer queries considering RDFS semantics. We also consider their embedding as extensions of SPARQL. These SPARQL extensions are interpreted within the proposed framework and their drawbacks are presented. In particular, we show that the PSPARQL query language, a strict extension of SPARQL offering transitive closure, allows for answering SPARQL queries modulo RDFS graphs with the same complexity as SPARQL through a simple transformation of the queries. We also consider languages which, in addition to paths, provide constraints. In particular, we present and compare nSPARQL and our proposal CPSPARQL. We show that CPSPARQL is expressive enough to answer full SPARQL queries modulo RDFS. Finally, we compare the expressiveness and complexity of both nSPARQL and the corresponding fragment of CPSPARQL, that we call cpSPARQL. We show that both languages have the same complexity through cpSPARQL, being a proper extension of SPARQL graph patterns, is more expressive than nSPARQL.Comment: RR-8394; alkhateeb2003

Constrained regular expressions for answering RDF-path queries modulo RDFS

alkhateeb2014aInternational audienceThe standard SPARQL query language is currently defined for querying RDF graphs without RDFS semantics. Several extensions of SPARQL to RDFS semantics have been proposed. In this paper, we discuss extensions of SPARQL that use regular expressions to navigate RDF graphs and may be used to answer queries considering RDFS semantics. In particular, we present and compare nSPARQL and our proposal CPSPARQL. We show that CPSPARQL is expressive enough to answer full SPARQL queries modulo RDFS. Finally, we compare the expressiveness and complexity of both nSPARQL and the corresponding frag- ment of CPSPARQL, that we call cpSPARQL. We show that both languages have the same complexity through cpSPARQL, being a proper extension of SPARQL graph patterns, is more expressive than nSPARQL

Query answering in distributed description logics

alkhateeb2007aInternational audienceThis paper describes the notion of query answering in a distributed knowledge based system, and gives methods for computing these answers in certain cases. More precisely, given a distributed system (DS) of ontologies and ontology mappings (or bridge rules) written in Distributed Description Logics (DDL), distributed answers are defined for queries written in terms of one particular ontology. These answers may contain individuals from different ABoxes. To compute these answers, the paper provides an algorithm that reduce the problem of distributed query answering to local query answering. This algorithm is proved correct but not complete in the general case

Complex path queries for RDF graphs

alkhateeb2005aInternational audienceNo abstract available

RDF with regular expressions

RDF is a knowledge representation language dedicated to the annotation of resources within the framework of the semantic web. Among the query languages for querying an RDF knowledge base, some, such as SPARQL, are based on the formal semantics of RDF and the concept of consequence semantic, others, inspired by the work in data bases, uses regular expressions making it possible to search the paths in the graph associated with the knowledge base. In order to combine the expressivity of these two approaches, we define a mixed language, called PRDF (for "Paths RDF") in which the arcs of a graph can be labeled by regular expressions. We define the syntax and the semantics of these objects, and propose a correct and complete algorithm which, by a kind of homomorphism, calculates the semantic consequence between an RDF graph and a PRDF graph. This algorithm is the heart of the extension of the SPARQL query language which we propose and implemented: a PSPARQL query allows to query an RDF knowledge base using graph patterns whose predicates are regular expressions

Artificial Bee Colony with Different Mutation Schemes: A comparative study

Artificial Bee Colony (ABC) is a swarm-based metaheuristic for continuous optimization. Recent work hybridized this algorithm with other metaheuristics in order to improve performance. The work in this paper, experimentally evaluates the use of different mutation operators with the ABC algorithm. The introduced operator is activated according to a determined probability called mutation rate (MR). The results on standard benchmark function suggest that the use of this operator improves performance in terms of convergence speed and quality of final obtained solution. It shows that Power and Polynomial mutations give best results. The fastest convergence was for the mutation rate value (MR=0.2)

Interroger RDF(S) avec des expressions régulières

RDF is a knowledge representation language dedicated to the annotation of resources within the Semantic Web. Though RDF itself can be used as a query language for an RDF knowledge base (using RDF semantic consequence), the need for added expressivity in queries has led to define the SPARQL query language. SPARQL queries are defined on top of graph patterns that are basically RDF graphs with variables. SPARQL queries remain limited as they do not allow queries with unbounded sequences of relations (e.g. "does there exist a trip from town A to town B using only trains or buses?"). We show that it is possible to extend the RDF syntax and semantics defining the PRDF language (for Path RDF) such that SPARQL can overcome this limitation by simply replacing the basic graph patterns with PRDF graphs, effectively mixing RDF reasoning with database-inspired regular paths. We further extend PRDF to CPRDF (for Constrained Path RDF) to allow expressing constraints on the nodes of traversed paths (e.g. "Moreover, one of the correspondences must provide a wireless connection."). We have provided sound and complete algorithms for answering queries (the query is a PRDF or a CPRDF graph, the knowledge base is an RDF graph) based upon a kind of graph homomorphism, along with a detailed complexity analysis. Finally, we use PRDF or CPRDF graphs to generalize SPARQL graph patterns, defining the PSPARQL and CPSPARQL extensions, and provide experimental tests using a complete implementation of these two query languages.RDF est un langage de représentation des connaissances dédié à l'annotation des ressources dans le Web Sémantique. Bien que RDF peut être lui-même utilisé comme un langage de requêtes pour interroger une base de connaissances RDF (utilisant la conséquence RDF), la nécessité d'ajouter plus d'expressivité dans les requêtes a conduit à définir le langage de requêtes SPARQL. Les requêtes SPARQL sont définies à partir des patrons de graphes qui sont fondamentalement des graphes RDF avec des variables. Les requêtes SPARQL restent limitées car elles ne permettent pas d'exprimer des requêtes avec une séquence non-bornée de relations (par exemple, Existe-t-il un itinéraire d'une ville A à une ville B qui n'utilise que les trains ou les bus?"). Nous montrons qu'il est possible d'étendre la syntaxe et la sémantique de RDF, définissant le langage PRDF (pour Path RDF) afin que SPARQL puisse surmonter cette limitation en remplaçant simplement les patrons de graphes basiques par des graphes PRDF. Nous étendons aussi PRDF à CPRDF (pour Constrained Path RDF) permettant d'exprimer des contraintes sur les sommets des chemins traversés (par exemple, "En outre, l'une des correspondances doit fournir une connexion sans fil."). Nous avons fourni des algorithmes corrects et complets pour répondre aux requêtes (la requête est un graphe PRDF ou CPRDF, la base de connaissances est un graphe RDF) basés sur un homomorphisme particulier, ainsi qu'une analyse détaillée de la complexité. Enfin, nous utilisons les graphes PRDF ou CPRDF pour généraliser les requêtes SPARQL, définissant les extensions PSPARQL et CPSPARQL, et fournissons des tests expérimentaux en utilisant une implémentation complète de ces deux langages

Une extension de RDF avec des expressions régulières

alkhateeb2007cNational audienceRDF est un langage de représentation de connaissances dédié à l'annotation de ressources dans le cadre du web sémantique. Parmi les langages de requêtes permettant d'interroger une base de connaissances RDF, certains, tels que SPARQL, s'appuient sur la sémantique formelle de RDF et la notion de conséquence sémantique, d'autres, inspirés par des travaux en bases de données, utilisent des expressions régulières permettant de chercher des chemins dans le graphe associé à la base de connaissances. Afin de conjuguer l'expressivité de ces deux approches, nous définissons un langage mixte, appelé PRDF (pour "Paths RDF") dans lequel les arcs d'un graphe peuvent être étiquetés par des expressions régulières. Nous définissons la syntaxe et la sémantique de PRDF, et proposons un algorithme correct et complet qui, par un homomorphisme particulière, calcule la conséquence sémantique entre un graphe RDF et un graphe PRDF. Cet algorithme est au c\oe{}ur de l'extension du langage de requêtes SPARQL que nous proposons et avons implémenté: une requête PSPARQL permet d'interroger une base de connaissances RDF en utilisant des patterns dont les prédicats sont des expressions régulières