Integrating Deep and Shallow Semantic Structures in Open Ontology Forge
This event took place on Friday 15 October 2004 at 13:30
Dr Nigel Collier National Institute of Informatics, Tokyo
Work in knowledge representation undertaken as part of the Semantic Web initiative has enabled a common infrastructure (Resource Description Framework (RDF) and RDF Schema) for sharing knowledge of ontologies and instances. In this talk I present a framework for combining the shallow levels of semantic description commonly used in MUC-style information extraction (IE) with the deeper semantic structures available in such ontologies. The framework is implemented within the PIA project software called Open Ontology Forge (OOF). OOF offers a rich desktop based environment for editing ontologies and large-scale capture of text and image annotations. It will also soon support a modular architecture for plug-ins which will allow IE components to reduce the effort making annotations by human experts. We discuss the knowledge framework, some features of the system and summarize work within our group on component IE technologies such as named entity, coreference and event annotation.
This event took place on Friday 15 October 2004 at 13:30
Work in knowledge representation undertaken as part of the Semantic Web initiative has enabled a common infrastructure (Resource Description Framework (RDF) and RDF Schema) for sharing knowledge of ontologies and instances. In this talk I present a framework for combining the shallow levels of semantic description commonly used in MUC-style information extraction (IE) with the deeper semantic structures available in such ontologies. The framework is implemented within the PIA project software called Open Ontology Forge (OOF). OOF offers a rich desktop based environment for editing ontologies and large-scale capture of text and image annotations. It will also soon support a modular architecture for plug-ins which will allow IE components to reduce the effort making annotations by human experts. We discuss the knowledge framework, some features of the system and summarize work within our group on component IE technologies such as named entity, coreference and event annotation.
Future Internet
KnowledgeManagementMultimedia &
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HypermediaNew Media SystemsSemantic 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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