External Publications
15 publications | pharos
Llorente, A. (2010) Semantics and Statistics for Automated Image Annotation PhD Thesis
Llorente, A., Motta, E. and Rueger, S. (2010) Exploring the Semantics Behind a Collection to Improve Automated Image Annotation, Proceedings of the 10th Workshop of the Cross-Language Evaluation Forum (CLEF 2009), LCNS 6242, Part II, Springer
Llorente, A., Manmatha, R. and Rueger, S. (2010) Image Retrieval using Markov Random Fields and Global Image Features, Proceedings of the ACM International Conference on Image and Video Retrieval, Xi'an, China, pp. 243-250
Nowak, S., Llorente, A., Motta, E. and Rueger, S. (2010) The Effect of Semantic Relatedness Measures on Multi-label Classification Evaluation, Proceedings of the ACM International Conference on Image and Video Retrieval, Xi'an, China, pp. 303-310
Llorente, A., Motta, E. and Rueger, S. (2009) Image Annotation Refinement using Web-based Keyword Correlation, Proceedings of the 4th International Conference on Semantic and Digital Media Technologies, Graz, Austria, 5887, pp. 188--191
Liu, H., Zagorac, S., Uren, V., Song, D. and Rueger, S. (2009) Enabling Effective User Interactions in Content-Based Image Retrieval, The 5th Asia Information Retrieval Symposium (AIRS2009), Sapporo, Japan, pp. 265-276, Springer
Little, S. and Rueger, S. (2009) Conservation of Effort in Feature Selection for Image Annotation, Workshop: IEEE Multimedia Signals Processing (MMSP), Brazil
Llorente, A., Little, S. and Rueger, S. (2009) MMIS at ImageCLEF 2009: Non-parametric Density Estimation Algorithms, Working notes for the CLEF 2009 Workshop, Corfu, Greece
Llorente, A. and Rueger, S. (2009) Using Second Order Statistics to Enhance Automated Image Annotation, Proceedings of the 31st European Conference on Information Retrieval, Toulouse, France, 5478, pp. 570-577
Llorente, A. and Rueger, S. (2008) Can a Probabilistic Image Annotation System be Improved Using a Co-occurrence Approach?, Proceedings of the Workshop on Cross-Media Information Analysis, Extraction and Management, Koblenz, Germany, 437, pp. 33-42
Llorente, A., Zagorac, S., Little, S., Hu, R., Kumar, A., Shaik, S., Ma, X. and Rueger, S. (2008) Semantic Video Annotation using Background Knowledge and Similarity-based Video Retrieval, TREC Video Retrieval Evaluation Notebook Papers, Gaithersburg, Maryland, NIST
Llorente, A., Overell, S., Liu, H., Hu, R., Rae, A., Zhu, J., Song, D. and Rueger, S. (2008) Exploiting Term Co-occurrence for Enhancing Automated Image Annotation, Proceedings of the 9th Workshop of the Cross-Language Evaluation Forum (CLEF 2008), LNCS 5706, pp. 632--639, Springer
Overell, S., Llorente, A., Liu, H., Hu, R., Rae, A., Zhu, J., Song, D. and Rueger, S. (2008) MMIS at ImageCLEF 2008: Experiments combining Different Evidence Sources, Working notes for the CLEF 2008 Workshop, Aarhus, Denmark
Liu, H., Song, D., Rueger, S., Hu, R. and Uren, V. (2008) Comparing Dissimilarity Measures for Content-based Image Retrieval, The 4th Asia Information Retrieval Symposium (AIRS2008), Harbin, China, pp. 44-50, Springer
Huang, Z., Shen, H., Zhou, X., Song, D. and Rueger, S. (2007) Dimensionality Reduction for Dimension-specific Search, Poster at The 30th Annual International ACM SIGIR Conference (SIGIR'2007), pp. 849-850
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Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
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