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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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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