21 research outputs found

    Contribution to the elaboration of a decision support system based on modular ontologies for ecological labelling

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    With the rising concern of sustainability and environmental performance, eco-labeled products and services are becoming more and more popular. In addition to the financial costs, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. In this research work, we propose a decision support process and implement a decision support platform aiming at further improvement and acceleration of the eco-labeling process in order to democratize a broader application and certification of eco-labels. The decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to official eco-label criteria documentation. Traditional knowledge base in relational data model is low interoperable, lack of inference support and difficult to be reused. In our research, the knowledge base composed of interconnected ontologies modules covers various products and services, and allows reasoning and semantic querying. A domain-centric modularization scheme about EU Eco-label laundry detergent product criteria is introduced as an application case. This modularization scheme separates the entity knowledge and rule knowledge so that the ontology modules can be reused easily in other domains. We explore a reasoning methodology based on inference with SWRL (Semantic Web Rule Language) rules which allows decision making with explanation. Through standard RDF (Resource Description Framework) and OWL (Web Ontology Language) ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other application. In order to foster the reuse of ontology modules, we also proposed a usercentric approach for federate contextual ontologies (mapping and integration). This approach will create an ontology federation by a contextual configuration that avoid the “OWL:imports” disadvantages. Instead of putting mapping or new semantics in ontology modules, our approach will conserve the extra contextual information separately without impacting original ontologies or without importing all ontologies’ concepts. By introducing this contextualization, it becomes easier to support more expressive semantics in term of ontology integration itself, then it will also facilitate application agents to access and reuse ontologies. To realize this approach, we elaborate a new plug-in for the ProtĂ©gĂ© ontology editor

    Flexible query processing for SPARQL

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    Flexible querying techniques can enhance users' access to complex, heterogeneous datasets in settings such as Linked Data, where the user may not always know how a query should be formulated in order to retrieve the desired answers. This paper presents query processing algorithms for a fragment of SPARQL 1.1 incorporating regular path queries (property path queries), extended with query approximation and relaxation operators. Our flexible query processing approach is based on query rewriting and returns answers incrementally according to their ``distance'' from the exact form of the query. We formally show the soundness, completeness and termination properties of our query rewriting algorithm. We also present empirical results that show promising query processing performance for the extended language

    Answering Pattern Queries Using Views

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    Approximation and relaxation of semantic web path queries

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    Given the heterogeneity of complex graph data on the web, such as RDF linked data, it is likely that a user wishing to query such data will lack full knowledge of the structure of the data and of its irregularities. Hence, providing flexible querying capabilities that assist users in formulating their information seeking requirements is highly desirable. In this paper we undertake a detailed theoretical investigation of query approximation, query relaxation, and their combination, for this purpose. The query language we adopt comprises conjunctions of regular path queries, thus encompassing recent extensions to SPARQL to allow for querying paths in graphs using regular expressions (SPARQL 1.1). To this language we add standard notions of query approximation based on edit distance, as well as query relaxation based on RDFS inference rules. We show how both of these notions can be integrated into a single theoretical framework and we provide incremental evaluation algorithms that run in polynomial time in the size of the query and the data, returning answers in ranked order of their `distance' from the original query. We also combine for the first time these two disparate notions into a single `flex' operation that simultaneously applies both approximation and relaxation to a query conjunct, providing even greater flexibility for users, but still retaining polynomial time evaluation complexity and the ability to return query answers in ranked order

    Sur l'analyse statique des requĂȘtes SPARQL avec la logique modale

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    Static analysis is a core task in query optimization and knowledge base verification. We study static analysis techniques for SPARQL, the standard language for querying Semantic Web data. Specifically, we investigate the query containment problem and the query-update independence analysis. We are interested in developing techniques through reductions to the validity problem in logic.We address SPARQL query containment with optional matching. We focus on the class of well-designed SPARQL queries, proposed in the literature as a fragment of the language with good properties regarding query evaluation. SPARQL is interpreted over graphs, hence we encode it in a graph logic, specifically the modal logic K interpreted over label transition systems. We show that this logic is powerful enough to deal with query containment for the well-designed fragment of SPARQL. We show how to translate RDF graphs into transition systems and SPARQL queries into K-formulae. Therefore, query containment in SPARQL can be reduced to unsatisfiability in K.We also report on a preliminary overview of the SPARQL query-update problem. A query is independent of an update when the execution of the update does not affect the result of the query. Determining independence is especially useful in the contest of huge RDF repositories, where it permits to avoid expensive yet useless re-evaluation of queries. While this problem has been intensively studied for fragments of relational calculus, no works exist for the standard query language for the semantic web. We report on our investigations on how a notion of independence can be defined in the SPARQL contextL’analyse statique est une tĂąche essentielle dans l’optimisation des requĂȘtes et la vĂ©rification de la base de graphes RDF. Nous Ă©tudions des techniques d’analyse statique pour SPARQL, le langage standard pour l’interrogation des donnĂ©es du Web sĂ©mantique. Plus prĂ©cisĂ©ment, nous Ă©tudions le problĂšme d’inclusion des requĂȘtes et de l’analyse de l’indĂ©pendance entre les requĂȘtes et la mise Ă  jour de la base de graphes RDF.Nous sommes intĂ©ressĂ©s par le dĂ©veloppement de techniques grĂące Ă  des rĂ©ductions au problĂšme de la satisfaisabilitĂ© de la logique.Nous nous traitons le problĂšme d’inclusion des requĂȘtes SPARQL en prĂ©sence de l’opĂ©rateur OPTIONAL. L’optionalitĂ© est l’un des constructeurs les plus compliquĂ©s dans SPARQL et aussi celui qui rend ce langage plus expressif que les langages de requĂȘtes classiques, comme SQL.Nous nous concentrons sur la classe de requĂȘtes appelĂ©e "well-designed SPARQL", proposĂ©es dans la littĂ©rature comme un fragment du langage avec de bonnes propriĂ©tĂ©s en matiĂšre d’évaluation des requĂȘtes incluent l’opĂ©ration OPTIONAL. À ce jour, l’inclusion de requĂȘte a Ă©tĂ© testĂ©e Ă  l’aide de diffĂ©rentes techniques: homomorphisme de graphes, bases de donnĂ©es canoniques, techniques de la thĂ©orie des automates et rĂ©duction au problĂšme de la validitĂ© d’une logique. Dans cette thĂšse, nous utilisons la derniĂšre technique pour tester l’inclusion des requĂȘtes SPARQL avec OPTIONAL utilisant une logique expressive appelĂ©e «logique K». En utilisant cette technique, il est possible de rĂ©gler le problĂšme d’inclusion des requĂȘtes pour plusieurs fragment de SPARQL, mĂȘme en prĂ©sence de schĂ©mas. Cette extensibilitĂ© n’est pas garantie par les autres mĂ©thodes.Nous montrons comment traduire a graphe RDF en un systĂšme de transitions, ainsi que une requĂȘte SPARQL en une formula K. Avec ces traductions, l’inclusion des requĂȘtes dans SPARQL peut ĂȘtre rĂ©duite au test de la validitĂ© d’une formule logique. Un avantage de cette approche est d’ouvrir la voie pour des implĂ©mentations utilisant solveurs de satisfiabilitĂ© pour K.Nous prĂ©sentons un banc d’essais de tests d’inclusion pour les requĂȘtes SPARQL avec OPTIONAL. Nous avons effectuĂ© des expĂ©riences pour tester et comparer des solveurs d’inclusion de l’état de l’art.Nous prĂ©sentons Ă©galement un aperçu prĂ©liminaire du problĂšme d’indĂ©pendance entre requĂȘte et mise Ă  jour. Une requĂȘte est indĂ©pendante de la mise Ă  jour lorsque l’exĂ©cution de la mise Ă  jour ne modifie pas le rĂ©sultat de la requĂȘte. Bien que ce problĂšme ait Ă©tĂ© intensivement Ă©tudiĂ© pour des fragments de calcul relationnel, il n’existe pas de travaux pour le langage de requĂȘtes standard pour le web sĂ©mantique. Nous proposons une dĂ©finition de la notion de l’indĂ©pendance dans le contexte de SPARQL et nous Ă©tablissons des premiĂšres pistes de analyse statique dans certains situations d’inclusion entre une requĂȘte et une mise Ă  jour

    Constrained regular expressions for answering RDF-path queries modulo RDFS

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    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

    Answering graph pattern queries using views

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    Answering SPARQL queries modulo RDF Schema with paths

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    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

    Graph pattern matching on social network analysis

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    Graph pattern matching is fundamental to social network analysis. Its effectiveness for identifying social communities and social positions, making recommendations and so on has been repeatedly demonstrated. However, the social network analysis raises new challenges to graph pattern matching. As real-life social graphs are typically large, it is often prohibitively expensive to conduct graph pattern matching over such large graphs, e.g., NP-complete for subgraph isomorphism, cubic time for bounded simulation, and quadratic time for simulation. These hinder the applicability of graph pattern matching on social network analysis. In response to these challenges, the thesis presents a series of effective techniques for querying large, dynamic, and distributively stored social networks. First of all, we propose a notion of query preserving graph compression, to compress large social graphs relative to a class Q of queries. We then develop both batch and incremental compression strategies for two commonly used pattern queries. Via both theoretical analysis and experimental studies, we show that (1) using compressed graphs Gr benefits graph pattern matching dramatically; and (2) the computation of Gr as well as its maintenance can be processed efficiently. Secondly, we investigate the distributed graph pattern matching problem, and explore parallel computation for graph pattern matching. We show that our techniques possess following performance guarantees: (1) each site is visited only once; (2) the total network traffic is independent of the size of G; and (3) the response time is decided by the size of largest fragment of G rather than the size of entire G. Furthermore, we show how these distributed algorithms can be implemented in the MapReduce framework. Thirdly, we study the problem of answering graph pattern matching using views since view based techniques have proven an effective technique for speeding up query evaluation. We propose a notion of pattern containment to characterise graph pattern matching using views, and introduce efficient algorithms to answer graph pattern matching using views. Moreover, we identify three problems related to graph pattern containment, and provide efficient algorithms for containment checking (approximation when the problem is intractable). Fourthly, we revise graph pattern matching by supporting a designated output node, which we treat as “query focus”. We then introduce algorithms for computing the top-k relevant matches w.r.t. the output node for both acyclic and cyclic pattern graphs, respectively, with early termination property. Furthermore, we investigate the diversified top-k matching problem, and develop an approximation algorithm with performance guarantee and a heuristic algorithm with early termination property. Finally, we introduce an expert search system, called ExpFinder, for large and dynamic social networks. ExpFinder identifies top-k experts in social networks by graph pattern matching, and copes with the sheer size of real-life social networks by integrating incremental graph pattern matching, query preserving compression and top-k matching computation. In particular, we also introduce bounded (resp. unbounded) incremental algorithms to maintain the weighted landmark vectors which are used for incremental maintenance for cached results
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