TUD-MMC at MediaEval 2016: Context of Experience task

This paper provides a three-step framework to predict user assessment of the suitability of movies for an inflight viewing context. For this, we employed classifier stacking strategies. First of all, using the different modalities of training data, twenty-one classifiers were trained together with a feature selection algorithm. Final predictions were then obtained by applying three classifier stacking strategies. Our results reveal that different stacking strategies lead to different evaluation results. A considerable improvement can be found for the F1-score when using the label stacking strategy.