Non-standard inference services in Description Logics for semantically annotated resource retrieval
This event took place on Thursday 05 May 2005 at 13:00
Tommaso Di Noia Information Technology Engineering, Politecnico di Bari, Italy
A semantically annotated resource is any kind of good, tangible or intangible (e.g. a document, a image, a product, a service) endowed of a description that refers to a shared ontology.
In this talk we present services that aim at fully exploiting the semantic annotation, to provide principled approximated resource retrieval. We introduce and motivate, in particular, services - based on the formal semantics of Description Logics languages - for resource ranking and/or composition using Concept Contraction and Concept Abduction.
Download PDF of Presentation (540kb ZIP file)
This event took place on Thursday 05 May 2005 at 13:00
A semantically annotated resource is any kind of good, tangible or intangible (e.g. a document, a image, a product, a service) endowed of a description that refers to a shared ontology.
In this talk we present services that aim at fully exploiting the semantic annotation, to provide principled approximated resource retrieval. We introduce and motivate, in particular, services - based on the formal semantics of Description Logics languages - for resource ranking and/or composition using Concept Contraction and Concept Abduction.
Download PDF of Presentation (540kb ZIP file)
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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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