Topic
Ontology-based data integration
About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.
Papers published on a yearly basis
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13 Nov 2010TL;DR: A Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology is developed, using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples and more temporal information and relations can be inferred by Semantic Web based reasoning tools.
Abstract: Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-based clinical narrative reports directly. We have developed a Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology. Using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples. More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully.
72 citations
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01 Jul 2011TL;DR: This paper presents the approach to extract relevant ontology concepts and their relationships from a knowledge base of heterogeneous text documents and shows the architecture of the implemented system and discusses the experiments in a real-world context.
Abstract: Ontologies have been frequently employed in order to solve problems derived from the management of shared distributed knowledge and the efficient integration of information across different applications However, the process of ontology building is still a lengthy and error-prone task Therefore, a number of research studies to (semi-)automatically build ontologies from existing documents have been developed In this paper, we present our approach to extract relevant ontology concepts and their relationships from a knowledge base of heterogeneous text documents We also show the architecture of the implemented system and discuss the experiments in a real-world context
72 citations
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01 Jan 2004
TL;DR: This paper presents a method that is based on formal concept analysis, which is a theory of data analysis which identifies conceptual structures among data sets which leads to an ontology that is suitable for knowledge exchange.
Abstract: Ontologies, often defined as an explicit specification of conceptualization, are necessary for knowledge representation and knowledge exchange. Usually this means that ontology describes concepts and relations that exist in a domain. To enable knowledge exchange, it is necessary to describe these concepts and relations in a better way than just ordering them in taxonomy. However, ontology design usually starts and stops with designing taxonomies. We present a method that is based on formal concept analysis, which is a theory of data analysis which identifies conceptual structures among data sets. This method allows for discovering necessity for new concepts and relations in an ontology, which leads to an ontology that has these entities described in a way suitable for knowledge exchange.
72 citations
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08 May 2006TL;DR: This work proposes a layered communication protocol which incorporates techniques for ontology exchange and shows how these agents successfully exchange information on news articles, despite initial difficulties raised by heterogeneous ontologies.
Abstract: Communication in open heterogeneous multi agent systems is hampered by lack of shared ontologies. To overcome these problems, we propose a layered communication protocol which incorporates techniques for ontology exchange. Using this protocol, the agents gradually build towards a semantically integrated system by establishing minimal and effective shared ontologies. We tested our approach, called ANEMONE, on a number of heterogeneous news agents. We show how these agents successfully exchange information on news articles, despite initial difficulties raised by heterogeneous ontologies.
72 citations