Approximation for the Semantic Web
This event took place on Friday 05 May 2006 at 12:30
Dr. Holger Wache Vrije Universiteit Amsterdam
Scalable reasoning for the Semantic Web is a crucial issue. Without scalability the Semantic Web will not be able to reason about the high and growing amount of data with respect to time performance and tolerant reasoning. Approximate reasoning seems to be a promising approach to introduce scalability to the Semantic Web.
Different forms of approximated reasoning are possible. First the reasoning process itself can be approximated by replacing the inference engine by a sophisticated approximated one. Second the knowledge, i.e. the ontology, can be weakened or, third, translated into another representation formalism. Obviously during both transformations knowledge is lost.
This talk reports about the investigation and experiences made in KNOWLEDGEWEB, an EU-funded network of excellence. The logical foundation of some approaches is briefly explained but also their practical consequences for scalable reasoning will be investigated.
Download Presentation Slides.
This event took place on Friday 05 May 2006 at 12:30
Scalable reasoning for the Semantic Web is a crucial issue. Without scalability the Semantic Web will not be able to reason about the high and growing amount of data with respect to time performance and tolerant reasoning. Approximate reasoning seems to be a promising approach to introduce scalability to the Semantic Web.
Different forms of approximated reasoning are possible. First the reasoning process itself can be approximated by replacing the inference engine by a sophisticated approximated one. Second the knowledge, i.e. the ontology, can be weakened or, third, translated into another representation formalism. Obviously during both transformations knowledge is lost.
This talk reports about the investigation and experiences made in KNOWLEDGEWEB, an EU-funded network of excellence. The logical foundation of some approaches is briefly explained but also their practical consequences for scalable reasoning will be investigated.
Download Presentation Slides.
Future Internet
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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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