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Tech Report kmi-01-14 Abstract


Beyond Rigid KA Metatools: An Initial Proposal for a KR-Independent, Adaptive, Customizable, Ontology-based KA Metatool
Techreport ID: kmi-01-14
Date: 2001
Author(s): Yuangui lei, Enrico Motta and John Domingue
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This paper proposes a new knowledge-acquisition metatool, KRIACO, a Web-based, Knowledge Representation Independent, Adaptive, Customizable, Ontology-based Knowledge Acquisition Metatool, which aims to overcome sorts of shortcomings of current knowledge acquisition metatools. To achieve its goal, KRIACO will adopt OKBC as an underlying knowledge representation model to overcome the restriction caused by a specific knowledge representation system. It will use an ontology-driven tool specification approach to specify the domain and the task models; an interface ontology and a declarative interface model to drive the interface design and customization process; adaptive approach to provide flexible, adaptive user interfaces. This paper discusses these approaches in detail and presents the framework of KRIACO.
 
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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