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Tech Report kmi-08-05 Abstract


Probabilistic Methods for Data Integration in a Multi-Agent Query Answering System
Techreport ID: kmi-08-05
Date: 2008
Author(s): Miklos Nagy, Maria Vargas-Vera, Enrico Motta
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This report describes the progress that has been achieved during the second year (full time equivalent 1 July 2006 - 1 July 2008) of our Ph.D. research. All the work has been built upon the achievements of the first year and confirmed that the original research objectives were correctly identified at the beginning of the research. We have successfully participated in the Ontology Mapping Evaluation Initiative 2006 and 2007 (2008 ongoing activity), which provided a qualitative comparison of our and other ontology mapping systems. Further it created a possibility to identify our future research work that needs to be carried out in order to achieve our original research objectives that were set out in the formal Ph.D. research proposal. The organization of this report corresponds to original research proposal. The last section describes the thesis outline.
 
KMi Publications 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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