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Дисертації з теми "Fusion d'Ontologie":
Ma, Truong-Thanh. "Sur la fusion d'ontologies à domaine ouvert." Electronic Thesis or Diss., Artois, 2022. http://www.theses.fr/2022ARTO0406.
The subject of the thesis is ontology merging, an approach for integrating various ontology sources into a unique one that handles emerging conflicts. This dissertation takes inspiration from the belief merging theory for merging ontologies to produce a consistent and unified knowledge base. We propose the three following contributions.The first one is a semantic-based merging approach. In particular, a model-based merging strategy mainly focuses on handling semantic conflicts. A semantic conflict, which is not necessarily logical, is knowledge represented in many different or opposite ways. We also propose a formal model characterization and show the method's effectiveness with an experimental evaluation.The second approach proposes a new framework to merge open-domain terminological knowledge. It leverages RCC5, a formalism for representing regions in a topological space and reasoning about their set-theoretic relationships. We propose a faithful translation of terminological knowledge from conflicting sources into region spaces. Here, we merge knowledge bases in this space and translate the outcome into the input sources' language. Our technique uses RCC5's expressivity and flexibility to deal with contradictory knowledge.The last contribution is a framework for evaluating ontology merging operators. The primary strategy starts with an original ontology to create noisy ontologies as datasets and use them to assess the merging operators. Then, we analyze merging operators' computation time effectiveness and ability to cover the original ontology. Finally, we experimented with practical ontologies to evaluate the merging operators
Amarger, Fabien. "Vers un système intelligent de capitalisation de connaissances pour l'agriculture durable : construction d'ontologies agricoles par transformation de sources existantes." Thesis, Toulouse 2, 2015. http://www.theses.fr/2015TOU20138/document.
The data available on the Web are generally of two kinds: (1) non structured data or semi structured data, which are difficult to exploit automatically; or (2) structured data, dedicated to a specific usage, which are difficult to reuse for a different application. The Linked Open Data is a Semantic Web application facilitating access, share ability and alignment of data. There are many data available on the Web, but these are not always published using the Linked Open Data theory and thus need to be transformed into knowledge bases. An innovative methodology is proposed in this work: one that transforms several sources simultaneously, not sequentially. This methodology merges several data sources oriented by domain design patterns and defines the expected domain representation using the upper part of an ontological module. A process chain enriches this module with elements from the sources: syntactic transformation of the sources, alignment, identification of equivalent elements for the construction of candidates, computation of the candidates’ trust scores and candidate filtering. This work is based on the following hypothesis: if an element appears in several sources then the possibility that it belongs to the studied domain is increased. Several functions were defined in order to compute the consensual trust score of a specific candidate by bringing out such characteristics as the consensus between the sources or the connectivity between the elements within a given candidate. A second hypothesis is put forward: to obtain a valid design, an element must be part of one candidate only. This hypothesis resulted in the definition of the notion of incompatibility between the candidates. The extraction of the candidates that do not share elements can then be considered, which made the experts’ validation task easier. To evaluate the proposals, three experiments were conducted. The first one dealt with the taxonomic classification of wheat. With the assistance of three experts, this experiment made for the analysis of the validation of the generated candidates. The second experiment, still in the same domain, lead to the evaluation of the time an expert saved using the notion of incompatibility during the validation of the candidates. As for the last experiment, the data from an evaluation campaign of alignment systems were used. These data had to be adapted to evaluate the generation of the candidates and the definition of the consensual trust score on a large data set. These three proposals were implemented in a new reusable and configurable tool: Muskca. This tool allows a multi-source fusion for the generation of a consensual knowledge base. This methodology was applied to agriculture, which allowed the creation of a knowledge base on plant taxonomy. The knowledge base will be used to represent the observations of pest attacks on crops along with pest treatment techniques. Not only will this knowledge base help the publication of the available data but it will also allow the annotation of the various documents that will be used, so as to improve agricultural practices
Mahfoudh, Mariem. "Adaptation d'ontologies avec les grammaires de graphes typés : évolution et fusion." Thesis, Mulhouse, 2015. http://www.theses.fr/2015MULH1519/document.
Ontologies are a formal and explicit knowledge representation. They represent a given domain by their concepts and axioms while creating a consensus between a user community. To satisfy the new requirements of the represented domain, ontologies have to be regularly updated and adapted to maintain their consistency. The adaptation may take different forms (evolution, alignment, merging, etc.), and represents several scientific challenges. One of the most important is to preserve the consistency of the ontology during the changes. To address this issue, we are interested in this thesis to study the ontology changes and we propose a formal framework that can evolve and merge ontologies without affecting their consistency.First we propose TGGOnto (Typed Graph Grammars for Ontologies), a new formalism for the representation of ontologies and their changes using typed graph grammars (TGG). A coupling between ontologies and TGG is defined in order to take advantage of the graph grammars concepts, such as the NAC (Negative Application Conditions), in preserving the adapted ontology consistency. Second, we propose EvOGG (Evolving Ontologies with Graph Grammars), an ontology evolution approach that is based on the TGGOnto formalism that avoids inconsistencies using an a priori approach. We focus on OWL ontologies and we address both : (1) ontology enrichment by studying their structural level and (2) ontology population by studying the changes affecting individuals and their assertions. EvOGG approach defines different types of ontology changes (elementary, composite and complex) and ensures their implementation by the algebraic approach of graph transformation, SPO (Single pushout).Third, we propose GROM (Graph Rewriting for Ontology Merging), an ontologies merging approach that avoids data redundancy and reduces conflict in the merged result. The proposed approach consists of three steps: (1) the similarity search between concepts based on syntactic, structural and semantic techniques; (2) the ontologies merging by the algebraic approach SPO; (3) the global ontology adaptation with graph rewriting rules.To validate our proposals, we have developed several open source tools based on AGG (Attributed Graph Grammar) tool. These tools were applied to a set of ontologies, mainly on those developed in the frame of the CCAlps (Creatives Companies in Alpine Space) European project, which funded this thesis work
Navarrete, Terrassa Antonio 1973. "Semantic integration of thematic geographic information in a multimedia context." Doctoral thesis, Universitat Pompeu Fabra, 2006. http://hdl.handle.net/10803/7534.
Los datasets geográficos representan la realidad mediante un conjunto de entidades temáticas que a menudo no están definidas de una manera precisa y que diferentes sujetos pueden entender de distintas formas. La integración de información geográfica proveniente de diversas fuentes presenta un importante reto desde el punto de vista semántico. En esta tesis se propone una solución a este problema basada en la definición de un marco semántico cuyo núcleo es una ontología que representa los conceptos temáticos en un repositorio de datasets, así como las relaciones entre dichos conceptos. También se propone un método semi-automático para fusionar las ontologías de aplicación de los datasets en el repositorio. El marco semántico permite además la definición de servicios semánticos, en concreto la integración en un nuevo dataset de información temática proveniente de diversas fuentes. Finalmente, el marco semántico y sus servicios se utilizarán en un sistema de indexación y recuperación de elementos multimedia geo-referenciados a partir de su contenido geográfico temático.
Geographic datasets represent reality through a set of thematic entities that are often not precisely defined and that may be understood in different ways by different subjects. Integrating geographic information from diverse datasets presents an important challenge from the semantic point of view. A solution to this problem is proposed in this thesis based on the definition of a semantic framework whose core is an ontology that represents the thematic concepts in a repository of datasets as well as their relations. A semi-automatic method is also proposed to merge the application ontologies of the datasets in the repository. The semantic framework supports the definition of semantic services, particularly the integration of the thematic information from diverse datasets in a new one. Finally, the semantic framework and its services have been used in the context of indexing and retrieving geo-referenced multimedia elements based on their thematic geographic content.
Тези доповідей конференцій з теми "Fusion d'Ontologie":
Amrouch, Siham, and Sihem Mostefai. "Un algorithme semi-automatique pour la fusion d'ontologies basé sur la combinaison de stratégies." In 2012 International Conference on Education and e-Learning Innovations (ICEELI 2012). IEEE, 2012. http://dx.doi.org/10.1109/iceeli.2012.6360643.