Search (4 results, page 1 of 1)

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Abstract

This thesaurus-based search system uses automatic indexing, RDF-based querying, and concept-based visualization of results to support exploration of large online document repositories. Innovative research institutes rely on the availability of complete and accurate information about new research and development. Information providers such as Elsevier make it their business to provide the required information in a cost-effective way. The Semantic Web will likely contribute significantly to this effort because it facilitates access to an unprecedented quantity of data. The DOPE project (Drug Ontology Project for Elsevier) explores ways to provide access to multiple lifescience information sources through a single interface. With the unremitting growth of scientific information, integrating access to all this information remains an important problem, primarily because the information sources involved are so heterogeneous. Sources might use different syntactic standards (syntactic heterogeneity), organize information in different ways (structural heterogeneity), and even use different terminologies to refer to the same information (semantic heterogeneity). Integrated access hinges on the ability to address these different kinds of heterogeneity. Also, mental models and keywords for accessing data generally diverge between subject areas and communities; hence, many different ontologies have emerged. An ideal architecture must therefore support the disclosure of distributed and heterogeneous data sources through different ontologies. To serve this need, we've developed a thesaurus-based search system that uses automatic indexing, RDF-based querying, and concept-based visualization. We describe here the conversion of an existing proprietary thesaurus to an open standard format, a generic architecture for thesaurus-based information access, an innovative user interface, and results of initial user studies with the resulting DOPE system.

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Source

Journal on data semantics. 15(2011), S.158-192

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Series

Advanced information and knowledge processing

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Abstract

In this document we provide an overall view of the state of the art in ontology alignment. It is organised as a description of the need for ontology alignment, a presentation of the techniques currently in use for ontology alignment and a presentation of existing systems. The state of the art is not restricted to any discipline and consider as some form of ontology alignment the work made on schema matching within the database area for instance. Heterogeneity problems on the semantic web can be solved, for some of them, by aligning heterogeneous ontologies. This is illustrated through a number of use cases of ontology alignment. Aligning ontologies consists of providing the corresponding entities in these ontologies. This process is precisely defined in deliverable D2.2.1. The current deliverable presents the many techniques currently used for implementing this process. These techniques are classified along the many features that can be found in ontologies (labels, structures, instances, semantics). They resort to many different disciplines such as statistics, machine learning or data analysis. The alignment itself is obtained by combining these techniques towards a particular goal (obtaining an alignment with particular features, optimising some criterion). Several combination techniques are also presented. Finally, these techniques have been experimented in various systems for ontology alignment or schema matching. Several such systems are presented briefly in the last section and characterized by the above techniques they rely on. The conclusion is that many techniques are available for achieving ontology alignment and many systems have been developed based on these techniques. However, few comparisons and few integration is actually provided by these implementations. This deliverable serves as a basis for considering further action along these two lines. It provide a first inventory of what should be evaluated and suggests what evaluation criterion can be used.