Seminars [279]

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KMi Seminars
Using the Dempster-Shafer theory of evidence to resolve ABox inconsistencies
This event took place on Wednesday 07 November 2007 at 11:30

 
Andriy Nikolov Computing Research Centre, The Open University, UK

Automated ontology population using information extraction algorithms can produce inconsistent knowledge bases. Confidence values assigned by the extraction algorithms may serve as evidence helping to repair produced inconsistencies. Dempster-Shafer theory of evidence is a formalism, which allows appropriate interpretation of extractors’
confidence values. The talk presents an algorithm for translating the subontologies containing conflicts into belief propagation networks and repairing conflicts based on Dempster-Shafer plausibility.

 
KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Multimedia and Information Systems is...


Multimedia and Information Systems
Our research is centred around the theme of Multimedia Information Retrieval, ie, Video Search Engines, Image Databases, Spoken Document Retrieval, Music Retrieval, Query Languages and Query Mediation.

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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