Dominique Ritze

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State of the art ontology matching techniques are limited to detect simple correspondences between atomic concepts and properties. Nevertheless, for many concepts and properties atomic counterparts will not exist, while it is possible to construct equivalent complex concept and property descriptions. We define a correspondence where at least one of the(More)
Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind(More)
Ontology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind(More)
With a growing number of ontologies used in the semantic web, agents can fully make sense of different datasets only if correspondences between those ontologies are known. Ontology matching tools have been proposed to find such correspondences. While the current research focus is mainly on fully automatic matching tools, some approaches have been proposed(More)
A major challenge in information management today is the integration of huge amounts of data distributed across multiple data sources. A suggested approach to this problem is ontology-based data integration where legacy data systems are integrated via a common ontology that represents a unified global view over all data sources. However, data is often not(More)
Cross-domain knowledge bases such as DBpedia, YAGO, or the Google Knowledge Graph have gained increasing attention over the last years and are starting to be deployed within various use cases. However, the content of such knowledge bases is far from being complete, far from always being correct, and suffers from deprecation (i.e. population numbers become(More)
The Web contains vast amounts of HTML tables. Most of these tables are used for layout purposes, but a small subset of the tables is relational, meaning that they contain structured data describing a set of entities [2]. As these relational Web tables cover a very wide range of different topics, there is a growing body of research investigating the utility(More)
Current ontology matching techniques focus on detecting correspondences between atomic concepts and properties. Nevertheless, it is necessary and possible to detect correspondences between complex concept or property descriptions. In this paper, we demonstrate how complex matching can benefit from natural language processing techniques, and propose an(More)
This paper reports on the first usage of the MultiFarm dataset for evaluating ontology matching systems. This dataset has been designed as a comprehensive benchmark for multilingual ontology matching. In this first set of experiments, we analyze how state-of-the-art matching systems – not particularly designed for the task of multilingual ontology matching(More)