External Publications
6 publications | Smitashree Choudhury
Choudhury, S. and Breslin, J. (2011) Extracting Semantic Entities and Events from Sports Tweets, Workshop: Making Sense of Microposts (MSM2011)
Choudhury, S. and Breslin, J. (2010) Enriching Videos With Light Semantics, The Fourth International Conference on Advances in Semantic Processing. SEMAPRO 2010, Florence,Italy
Choudhury, S. and Breslin, J. (2010) User Sentiment Detection: A YouTube Use Case, The 21st National Conference on Artificial Intelligence and Cognitive Science, Galway,Ireland
Choudhury, S., Breslin, J. and Passant, A. (2009) Enrichment and Ranking of the YouTube Tag Space and Integration with the Linked Data Cloud, The 8th International Semantic Web Conference (ISWC 2009), LNCS Springer, Near Washington DC,USA
Choudhury, S., Breslin, J. and Decker, S. (2009) A Lightweight Web Video Model with Content and Context Descriptions for Integration with Linked Data, Workshop: Semantic Authoring, Annotation and Knowledge Markup Workshop (SAAKM) at 5th International Conference on Knowledge Capture (K-CAP 2009), Redondo Beach, California, USA
Choudhury, S. and Breslin, J. (2008) Using a Lightweight Multimedia Content Model for Semantic Annotation, 8th Annual Conference on Information Technology and Telecommunication, Galway,Ireland
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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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