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Tech Report kmi-09-05 Abstract


Open Services on the Web
Techreport ID: kmi-09-05
Date: 2009
Author(s): Maria Maleshkova
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The goal of the here described research is to explore the possibilities of combining Semantic Web technologies and fundamental Web principles, including URIs and HTTP, and to apply these on open services on the Web, in order to contribute to a Semantic Web, which is not only an extension of the current Web with more semantic descriptions of data but is rather more dynamic and seamlessly integrates services as sources of that data, which can be automatically discovered, composed and executed by the computer on behalf of its user. This document is the first year probation report of this PhD study on open services on the Web.

Publication(s):

Maleshkova, M., Kopecky, J., and Pedrinaci, C. (2009) Adapting SAWSDL for Semantic Annotations of RESTful Services, Workshop: Beyond SAWSDL at OnTheMove, OTM2009, Vilamoura, Portugal, OTM 2009 Workshops

Maleshkova, M., Pedrinaci, C., and Domingue, J. (2009) Supporting the Creation of Semantic RESTful Service Descriptions, Workshop: Service Matchmaking and Resource Retrieval in the Semantic Web (SMR2) at 8th International Semantic Web Conference, Proceedings of ISWC '09, Washington D.C., USA
 
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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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