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Tech Report kmi-03-01 Abstract


Semantic Layering with Magpie
Techreport ID: kmi-03-01
Date: 2003
Author(s): John Domingue, Martin Dzbor, Enrico Motta
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Browsing the web involves two main tasks: finding the right web page and then making sense of its content. A significant amount of research has gone into supporting the task of finding web resources through ‘standard’ information retrieval mechanisms, or semantics-enhanced search. Much less attention has been paid to the second problem. In this paper we describe Magpie, a tool which supports the interpretation of web pages. Magpie acts as a complementary knowledge source, which a reader can call upon to quickly gain access to any background knowledge relevant to a web resource. Magpie works by automatically associating an ontology based semantic layer to web resources, allowing relevant services to be directly invoked within a standard web browser. The functionality of Magpie is illustrated using examples of how it has been integrated with our lab’s web resources.

Publication(s):

An amended version of this report will appear as a chapter in the book on 'Ontologies in Information Systems' authored by Rudi Studer and Steffen Staab to be published by Springer Verlag soon.
 
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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