SCHEMA - Network of Excellence in Content-Based Semantic Scene Analysis and Information Retrieval Information Society Technologies
HomeProjectPartnersResultsUseful LinksLibrary

Project ConsortiumInformatics and Telematics InstituteTampere University of TechnologyBTexact TechnologiesUniversité Catholique de LouvainLaboratoire d’Informatique, Signaux et Systèmes de Sophia - AntipolisDublin City UniversityFratelli AlinariMunich University of TechnologyQueen Mary, University of LondonUniversitat Politecnica de CatalunyaFondazione Ugo BordoniUniversity of BresciaMacedonian Press Agency


Data and Knowledge Engineering Group, University of Queensland, Australia
The Data and Knowledge Engineering Group of the University of Queensland, Australia, works in the area of world-scale information systems. The technology is available to send bit strings from anywhere to anywhere, and for programs running in one place to communicate with programs running in another. People are building systems that cross organisational boundaries in such areas as supply chain management and collaborative bioinformatics. These applications involve a wide range of data types, some of which are extremely complex. The Data and Knowledge Engineering group, with its origins in the database world, is interested in the organisation of the content and behaviour of these world-scale information systems. This includes distributed enterprise computing, management of complex data types, and representation of the semantics of the information being exchanged and shared.

More specifically, the Data and Knowledge Engineering group identified three main areas of research concentration and strength: Distributed Enterprise Computing, Complex Data Management, and Semantic Issues.

Complex Data Management - main considerations revolve around performance and security issues on management, retrieval and knowledge discovery from very large amount of complex data, in particular for spatial, biological, multimedia and text data. The area of multimedia data mining with special emphasis on text and speech classification. Application domain also includes bioinformatics, spatial data, multimedia data, health and security and much of the software realisations embedded in search engines.

Prof. Xiaofang Zhou and his student Ms Ying Liu are working on large image database retrieval, specifically region-based image retrieval. With the integration of good image feature understanding and efficient data management technique, they aim to achieve fast and efficient region-based image database retrieval.

Contact person:
Prof. Xiaofang Zhou
School of Information Technology
& Electrical Engineering,
The University of Queensland
Brisbane QLD 4072 AUSTRALIA
(tel) +61 7 3365 3248
(fax) +61 7 3365 4999
e-mail: zxf@itee.uq.edu.au
http://www.itee.uq.edu.au/~infsys/



© 2002 SCHEMA (IST-2001-32795)
A project financed by the European Community