OLA in the OAEI 2007 evaluation contest

djoufak2007aInternational audienceSimilarity has become a classical tool for ontology confrontation motivated by alignment, mapping or merging purposes. In the definition of an ontologybased measure one has the choice between covering a single facet (e.g., URIs, labels, instances of an entity, etc.), covering all of the facets or just a subset thereof. In our matching tool, OLA, we had opted for an integrated approach towards similarity, i.e., calculation of a unique score for all candidate pairs based on an aggregation of all facet-wise comparison results. Such a choice further requires effective means for the establishment of importance ratios for facets, or weights, as well as for extracting an alignment out of the ultimate similarity matrix. In previous editions of the competition OLA has relied on a graph representation of the ontologies to align, OL-graphs, that reflected faithfully the syntactic structure of the OWL descriptions. A pair of OL-graphs was exploited to form and solve a system of equations whose approximate solutions were taken as the similarity scores. OLA2 is a new version of OLA which comprises a less integrated yet more homogeneous graph representation that allows similarity to be expressed as graph matching and further computed through matrix multiplying. Although OLA2 lacks key optimization tools from the previous one, while a semantic grounding in the form of WORDNET engine is missing, its results in the competition, at least for the benchmark test suite, are perceivably better

Descubrimiento automático de mappings

Dentro de la problemática de la integración de información, los elementos claves son los mappings, unidades que relacionan las diferentes representaciones (ontologías, bases de datos, redes semánticas, etc. ). Y dentro de toda la colección de operaciones que los mappings llevan asociadas en todo su ciclo de vida, el cuello de botella se encuentra en su descubrimiento. Con este trabajo doctoral se pretende dar un paso más en este campo realizando un nuevo modelo de mappings lo menos limitado, y a la vez funcional, posible a diferentes representaciones y lo más versátil para la combinación de técnicas de descubrimiento, de toda índole, ya existentes y de nuevo cuño de manera automática, basándose en un sistema experto previamente construido a costa de evaluaciones sobre casos de uso reales

The Role of String Similarity Metrics in Ontology Alignment

Tim Berners-Lee originally envisioned a much different world wide web than the one we have today - one that computers as well as humans could search for the information they need [3]. There are currently a wide variety of research efforts towards achieving this goal, one of which is ontology alignment

A Cooperative Approach for Composite Ontology Matching

Ontologies have proven to be an essential element in a range of applications in which knowl-edge plays a key role. Resolving the semantic heterogeneity problem is crucial to allow the interoperability between ontology-based systems. This makes automatic ontology matching, as an anticipated solution to semantic heterogeneity, an important, research issue. Many dif-ferent approaches to the matching problem have emerged from the literature. An important issue of ontology matching is to find effective ways of choosing among many techniques and their variations, and then combining their results. An innovative and promising option is to formalize the combination of matching techniques using agent-based approaches, such as cooperative negotiation and argumentation. In this thesis, the formalization of the on-tology matching problem following an agent-based approach is proposed. Such proposal is evaluated using state-of-the-art data sets. The results show that the consensus obtained by negotiation and argumentation represent intermediary values which are closer to the best matcher. As the best matcher may vary depending on specific differences of multiple data sets, cooperative approaches are an advantage. *** RESUMO - Ontologias são elementos essenciais em sistemas baseados em conhecimento. Resolver o problema de heterogeneidade semântica é fundamental para permitira interoperabilidade entre sistemas baseados em ontologias. Mapeamento automático de ontologias pode ser visto como uma solução para esse problema. Diferentes e complementares abordagens para o problema são propostas na literatura. Um aspecto importante em mapeamento consiste em selecionar o conjunto adequado de abordagens e suas variações, e então combinar seus resultados. Uma opção promissora envolve formalizara combinação de técnicas de ma-peamento usando abordagens baseadas em agentes cooperativos, tais como negociação e argumentação. Nesta tese, a formalização do problema de combinação de técnicas de ma-peamento usando tais abordagens é proposta e avaliada. A avaliação, que envolve conjuntos de testes sugeridos pela comunidade científica, permite concluir que o consenso obtido pela negociação e pela argumentação não é exatamente a melhoria de todos os resultados individuais, mas representa os valores intermediários que são próximo da melhor técnica. Considerando que a melhor técnica pode variar dependendo de diferencas específicas de múltiplas bases de dados, abordagens cooperativas são uma vantagem

SODA: an OWL-DL based ontology matching system

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Results of the Ontology Alignment Evaluation Initiative 2007

euzenat2007gInternational audienceWe present the Ontology Alignment Evaluation Initiative 2007 campaign as well as its results. The OAEI campaign aims at comparing ontology matching systems on precisely defined test sets. OAEI-2007 builds over previous campaigns by having 4 tracks with 7 test sets followed by 17 participants. This is a major increase in the number of participants compared to the previous years. Also, the evaluation results demonstrate that more participants are at the forefront. The final and official results of the campaign are those published on the OAEI web site

Argumentation over Ontology Correspondences in MAS

laera2007aInternational audienceIn order to support semantic interoperation in open environments, where agents can dynamically join or leave and no prior assumption can be made on the ontologies to align, the different agents involved need to agree on the semantics of the terms used during the interoperation. Reaching this agreement can only come through some sort of negotiation process. Indeed, agents will differ in the domain ontologies they commit to; and their perception of the world, and hence the choice of vocabulary used to represent concepts. We propose an approach for supporting the creation and exchange of different arguments, that support or reject possible correspondences. Each agent can decide, according to its preferences, whether to accept or refuse a candidate correspondence. The proposed framework considers arguments and propositions that are specific to the matching task and are based on the ontology semantics. This argumentation framework relies on a formal argument manipulation schema and on an encoding of the agents' preferences between particular kinds of arguments

Similarity recognition for OWL-based action recipes in RoboEarth

Sharing and integrating heterogeneous knowledge from different robots requires finding an agreement between the underlying abstract, hardware independent ontologies, saved in the RoboEarth cloud framework in the World Wide Web. A variety of methods from the literature may be used for this task, by means of similarity computation of two ontologies. While most of them come from other fields such as sequence alignment methods from the field of bioinformatics, they can be extended for ontology alignment purposes. While such methods basically perform a pair wise comparison of ontology entities, another approach called the OWL-Lite Alignment method uses a variety of different ontology alignment methods to integrate many ontology comparison techniques in one common framework. Both the sequence alignment based and OWL-Lite based solutions are presented and their suitability to conduct a similarity check for robot task descriptions upon an upload into the RoboEarth platform discussed

Construcción de un operador de Matching Ontológico para los niveles de representación semántico y semiótico

Este trabajo describe el diseño de un operador matching ontológico aplicable en el modelo conceptual propuesto por Chavarro (Chavarro, 2012), un diseño de cuatro capas que permite la configuración del operador de diferentes tipos de técnicas tanto a nivel de elemento como a nivel de estructura. El objetivo de este diseño es la creación de matcher ontológico de alto nivel adaptables a las necesidades de las ontologías con las cuales opera. Este trabajo presenta las primeras fases de construcción del operador y sus resultados preliminares

Construcción de un operador de Matching Ontológico para los niveles de representación semántico y semiótico

Este trabajo describe el diseño de un operador matching ontológico aplicable en el modelo conceptual propuesto por Chavarro (Chavarro, 2012), un diseño de cuatro capas que permite la configuración del operador de diferentes tipos de técnicas tanto a nivel de elemento como a nivel de estructura. El objetivo de este diseño es la creación de matcher ontológico de alto nivel adaptables a las necesidades de las ontologías con las cuales opera. Este trabajo presenta las primeras fases de construcción del operador y sus resultados preliminares