Création et mise à jour guidées d'objets dans une base RDF(S)

National audienceLa mise à jour des bases de connaissances existantes est cruciale pour tenir compte des nouvelles informations, régulièrement découvertes. Toutefois, en pratique, les données actuelles du Web Sémantique sont rarement mises à jour par les utilisateurs. Nous proposons UTILIS, une méthode pour aider les utilisateurs à ajouter de nouveaux objets. Un objet est une ressource de la base. Sa description correspond aux propriétés qu'il possède. Pendant la création d'un nouvel objet o, UTILIS recherche les objets similaires. Les propriétés des objets similaires sont utilisées comme suggestions pour complèter la description de o. Les objets similaires sont trouvés en appliquant des règles de relaxation à la description de o, prise comme une requête. Comparé avec l'état de l'art, la contribution est qu'UTILIS est à la fois incrémental, chaque nouvelle propriété est utilisée pour la recherche, et interactif, l'utilisateur a un rôle actif dans le processus

An Approach Towards Classifying and Navigating RDF data based on Pattern Structures

International audienceWith an increased interest in machine processable data, more and more data is now published in RDF (Resource Description Framework) format. This RDF data is present in independent and distributed resources which needs to be centralized, navigated and searched for domain specific applications. This paper proposes a new approach based on Formal Concept Analysis (FCA) to create a navigation space over semantic web data. This approach uses an extension of FCA and takes RDF triples and RDF Schema present on several independent sources and provide centralized access over the data resulting from several resources. Afterwards, SPARQL queries can be posed over this navigation space to access these distributed resources from one platform for information retrieval purposes

A Proposal for Extending Formal Concept Analysis to Knowledge Graphs

International audienceKnowledge graphs offer a versatile knowledge representation, and have been studied under different forms, such as conceptual graphs or Datalog databases. With the rise of the Semantic Web, more and more data are available as knowledge graphs. FCA has been successful for analyzing, mining, learning, and exploring tabular data, and our aim is to help transpose those results to graph-based data. Previous FCA approaches have already addressed relational data, hence graphs, but with various limits. We propose G-FCA as an extension of FCA where the formal context is a knowledge graph based on n-ary relationships. The main contributions is the introduction of " n-ary concepts " , i.e. concepts whose extents are n-ary relations of objects. Their intents, " projected graph patterns " , mix relationships of different arities, objects, and variables. In this paper, we lay first theoretical results, in particular the existence of a concept lattice for each concept arity, and the role of rela-tional projections to connect those different lattices

Interactive Exploration over RDF Data using Formal Concept Analysis

International audienceWith an increased interest in machine processable data, many datasets are now published in RDF (Resource Description Framework) format in Linked Data Cloud. These data are distributed over independent resources which need to be centralized and explored for domain specific applications. This paper proposes a new approach based on interactive data exploration paradigm using Pattern Structures, an extension of Formal Concept Analysis, to provide exploration and navigation over Linked Data through concept lattices. It takes RDF triples and RDF Schema based on user requirements and provides one navigation space resulting from several RDF resources. This navigation space allows user to navigate and search only the part of data that is interesting for her

Conceptual Navigation in Large Knowledge Graphs

International audienceA growing part of Big Data is made of knowledge graphs. Major knowledge graphs such as Wikidata, DBpedia or the Google Knowledge Graph count millions of entities and billions of semantic links. A major challenge is to enable their exploration and querying by end-users. The SPARQL query language is powerful but provides no support for exploration by endusers. Question answering is user-friendly but is limited in expressivity and reliability. Navigation in concept lattices supports exploration but is limited in expressivity and scalability. In this paper, we introduce a new exploration and querying paradigm, Abstract Conceptual Navigation (ACN), that merges querying and navigation in order to reconcile expressivity, usability, and scalability. ACN is founded on Formal Concept Analysis (FCA) by defining the navigation space as a concept lattice. We then instantiate the ACN paradigm to knowledge graphs (Graph-ACN) by relying on Graph-FCA, an extension of FCA to knowledge graphs. We continue by detailing how Graph-ACN can be efficiently implemented on top of SPARQL endpoints, and how its expressivity can be increased in a modular way. Finally, we present a concrete implementation available online, Sparklis, and a few application cases on large knowledge graphs

Desarrollo de un Sistema de recomendaciones para el fortalecimiento de competencias laborales a profesionales recién egresados usando Ontologías y RDFs

El Presente trabajo emplea las funcionalidades relativas a algunos componentes de la Web semántica, para habilitar interfaces Web que permiten mediante búsquedas SPARQL, obtener información de estudios complementarios a los perfiles de egresados recién graduados almacenados en la base de datos del sistema de información de egresados de la Universidad Nacional de Colombia. Dichos estudios complementarios serán recomendados mediante el procesamiento de transacciones almacenadas del módulo de bolsa de empleo, en el que los egresados más antiguos logran ser vinculados a procesos de contratación por parte de empresas que requieren cubrir vacantes a través del mismo sistema, luego de actualizar sus perfiles con trayectoria académica, experiencia laboral y perfil ocupacional. Este último elemento requiere de un etiquetado basado en herramientas de extracción y anotación en lenguaje natural, con el que se obtienen tripletas que permite búsquedas de perfiles afines a temáticas particulares demandadas por las empresas.Abstract: The present work uses the features relating to some components of the Semantic Web, to enable Web interfaces that allow searches SPARQL, information of complementary studies to the newly graduated alumni profiles stored in the database of the information system of graduates from the Universidad Nacional de Colombia. These studies will be recommended by the stored transaction processing module of employment, in which the oldest graduates can be linked to recruitment processes on the part of businesses that require filling vacancies through the same system, then update your profiles with academic career, work experience and occupational profile. This last item requires a labeling based on extraction and annotation tools in natural language, with the obtained triplets that allows searches of profiles related to particular themes demanded by companies.Maestrí

Conceptual Navigation in RDF Graphs with SPARQL-Like Queries

International audienceConcept lattices have been successfully used for information retrieval and browsing. They offer the advantage of combining querying and navigation in a consistent way. Conceptual navigation is more flexible than hierarchical navigation, and easier to use than plain querying. It has already been applied to formal, logical, and relational contexts, but its application to the semantic web is a challenge because of inference mechanisms and expressive query languages such as SPARQL. The contribution of this paper is to extend conceptual navigation to the browsing of RDF graphs, where concepts are accessed through SPARQL-like queries. This extended conceptual navigation is proved consistent w.r.t. the context (i.e., never leads to an empty result set), and complete w.r.t. the conjunctive fragment of the query language (i.e., every query can be reached by navigation only). Our query language has an expressivity similar to SPARQL, and has a more natural syntax close to description logics

Interrogation d'un réseau sémantique de documents : l'intertextualité dans l'accès à l'information juridique

A collection of documents is generally represented as a set of documents but this simple representation does not take into account cross references between documents, which often defines their context of interpretation. This standard document model is less adapted for specific professional uses in specialized domains in which documents are related by many various references and the access tools need to consider this complexity. We propose two models based on formal and relational concept analysis and on semantic web techniques. Applied on documentary objects, these two models represent and query in a unified way documents content descriptors and documents relations.Une collection documentaire est généralement représentée comme un ensemble de documents mais cette modélisation ne permet pas de rendre compte des relations intertextuelles et du contexte d'interprétation d'un document. Le modèle documentaire classique trouve ses limites dans les domaines spécialisés où les besoins d'accès à l'information correspondent à des usages spécifiques et où les documents sont liés par de nombreux types de relations. Ce travail de thèse propose deux modèles permettant de prendre en compte cette complexité des collections documentaire dans les outils d'accès à l'information. Le premier modèle est basée sur l'analyse formelle et relationnelle de concepts, le deuxième est basée sur les technologies du web sémantique. Appliquées sur des objets documentaires ces modèles permettent de représenter et d'interroger de manière unifiée les descripteurs de contenu des documents et les relations intertextuelles qu'ils entretiennent