TV ad video categorization with probabilistic latent concept learning
Proceedings of the international workshop on Workshop on multimedia information retrieval
Semantic modelling using TV-anytime genre metadata
EuroITV'07 Proceedings of the 5th European conference on Interactive TV: a shared experience
Discrimination of media moments and media intervals: sticker-based watch-and-comment annotation
Multimedia Tools and Applications
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In order to extract the atmosphere in media, we model the latent semantics of TV synopses and affective terms as patterns of emotional components. Using a selection of affective last.fm tags and TV-Anytime atmosphere terms as emotional buoys, we apply LSA latent semantic analysis to represent the correlation of terms and descriptions in a vector space that reflects the emotional context. Analyzing the resulting patterns of affective components, we propose that this approach could be applied to automatically generate affective user preferences based on synopsis, subtitles or other textual representations associated with media.