KANNEL: a Framework for Detecting and Managing Relations between Ontologies in Large Ontology Repository.
This event took place on Wednesday 27 May 2009 at 11:30
Carlo Alloca KMi, The Open University
Ontologies are the pillars of the Semantic Web (SW) and, as more and more ontologies are made available online, the SW is quickly taking shape. As a result, the research community is becoming more and more aware that ontologies are not isolated artifacts: they are, explicitly or implicitly, related with each other. Indeed, a number of studies have intended to tackle some of the challenges raised by ontology relationships, from both theoretical and practical points of view. We propose and describe KANNEL, a framework for detecting and managing semantic relations between ontologies for large ontology repositories. It is based on the DOOR ontology. Basically, it is a semantic structure (ontology with rules), which represents and formalizes important ontology relations on the Semantic Web. Making explicit implicit relations between ontologies provides meta-information that facilitates the development of Semantic Web Applications. In addiction, applied in the context of a large collection of automatically crawled ontologies, DOOR and KANNEL provide a starting point for analyzing the underlying structure of the network of ontologies that is the Semantic Web.
This event took place on Wednesday 27 May 2009 at 11:30
Ontologies are the pillars of the Semantic Web (SW) and, as more and more ontologies are made available online, the SW is quickly taking shape. As a result, the research community is becoming more and more aware that ontologies are not isolated artifacts: they are, explicitly or implicitly, related with each other. Indeed, a number of studies have intended to tackle some of the challenges raised by ontology relationships, from both theoretical and practical points of view. We propose and describe KANNEL, a framework for detecting and managing semantic relations between ontologies for large ontology repositories. It is based on the DOOR ontology. Basically, it is a semantic structure (ontology with rules), which represents and formalizes important ontology relations on the Semantic Web. Making explicit implicit relations between ontologies provides meta-information that facilitates the development of Semantic Web Applications. In addiction, applied in the context of a large collection of automatically crawled ontologies, DOOR and KANNEL provide a starting point for analyzing the underlying structure of the network of ontologies that is the Semantic Web.
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We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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