Titlebook: Semantic Multimedia; Second International Bianca Falcidieno,Michela Spagnuolo,Paul Buitelaar Conference proceedings 2007 Springer-Verlag Be

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Automatic Recommendations for Machine-Assisted Multimedia Annotation: A Knowledge-Mining Approachon rule mining as an underlying technology for a recommender system aimed at improving the annotation process of multimedia news documents. The accuracy of these systems is very sensitive to the number of already annotated news items (the ”cold-start”- problem); ontology-based semantic relations are being used to alleviate this situation.

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Thesaurus-Based Ontology on Image Analysisg image analysis thesaurus. Such an ontology could be used to support a wide range of tasks, including automated image analysis, algorithmic knowledge reuse, intelligent information retrieval, etc. Main steps and first results of the ontology development process are described.

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Personalization of Content in Virtual Exhibitionse users through their interaction. The proposed framework uses stereotypes to initialize user models, adapts user profiles dynamically and clusters users into interest groups. A 3D virtual museum has been implemented as a case study, and an evaluation has been conducted.

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Improving the Accuracy of Global Feature Fusion Based Image Categorisationte-of-the-art accuracy of supervised categorising of these images could be improved significantly by fusion of a large number of global image features. In this work, we preserve the general framework, but improve the components of the system: we modify the set of image features to include interest p

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Stopping Region-Based Image Segmentation at Meaningful Partitionself and when combined with the recently proposed approaches to . segmentation can produce results aligned with the most salient semantic regions/objects present in the scene across heterogeneous image collections. The method identifies a single iteration from the merging process as the stopping poin

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Hierarchical Long-Term Learning for Automatic Image Annotationrs’ query and browsing patterns are retained over multiple sessions, is used to guide the propagation of keywords onto image regions based on low-level feature distances. We demonstrate how singular value decomposition (SVD), normally used with latent semantic analysis (LSA), can be used to reconstr