Event detection from image hosting services by slightly-supervised multi-span context models

We present a method to detect social events in a set of pictures from an image hosting service (Flickr). This method relies on the analysis of user-generated tags, by using statistical models trained on both a small set of manually annotated data and a large data set collected from the Internet. Social event modeling relies on multi-span topic model based on LDA (Latent Dirichlet Allocation). Experiments are conducted in the experimental setup of MediaEval´2011 evaluation campaign. The proposed system outperforms significantly the best system of this benchmark, reaching a F-measure score of about 71%.