External Publications
7 publications | flor
Angeletou, S., Sabou, M. and Motta, E. (2009) Improving Folksonomies using Formal Knowledge: A Case Study on Search, 4th Asian Semantic Web Conference, Shanghai, China
Angeletou, S., Sabou, M. and Motta, E. (2009) Improving Search in Folksonomies: A Task Based Comparison of WordNet and Ontologies, Poster at The Fifth International Conference on Knowledge Capture, Proc. of The 5th International Conference on Knowledge Capture
Angeletou, S., Sabou, M. and Motta, E. (2009) Folksonomy Enrichment and Search, Demo at 6th European Semantic Web Conference, 6th European Semantic Web Conference, Heraklion, Crete 6th European Semantic Web Conference, Proc. of 6th European Semantic Web Conference
Angeletou, S. (2008) Semantic Enrichment of Folksonomy Tagspaces, International Semantic Web Conference, Doctoral Consortium, Karlsruhe, Germany Proc. ISWC'08
Angeletou, S., Sabou, M. and Motta, E. (2008) Semantically Enriching Folksonomies with FLOR, Workshop: 1st International Workshop on Collective Semantics: Collective Intelligence & the Semantic Web (CISWeb 2008) at European Semantic Web Conference
d'Aquin, M., Motta, E., Sabou, M., Angeletou, S., Gridinoc, L., Lopez, V. and Guidi, D. (2008) Towards a New Generation of Semantic Web Applications, IEEE Intelligent Systems, 23, 3, pp. 20-28
Angeletou, S., Sabou, M., Specia, L. and Motta, E. (2007) Bridging the Gap Between Folksonomies and the Semantic Web: An Experience Report, Workshop: Bridging the Gap between Semantic Web and Web 2.0 at European Semantic Web Conference
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Multimedia and Information Systems is...
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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