Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series; 28th International C Igor V. Tetko,Věra K?rková,Fabian

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Jointly Learning to Detect Emotions and Predict Facebook Reactionss, ranging from Computer Vision to Natural Language Processing. In this paper we focus on Facebook posts paired with “reactions” of multiple users, and we investigate their relationships with classes of emotions that are typically considered in the task of emotion detection. We are inspired by the i

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Materials Integration Strategies,ar spot in a video, an advertisement should be placed such that most people will watch more of the ad. This is done using emotion, text, action, audio and video analysis of different scenes of a video under consideration.

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https://doi.org/10.1007/978-3-642-60293-1proach outperforms many competitive sentiment classification baseline methods. Detailed analysis demonstrates the effectiveness of the proposed surrounding-based long-short memory neural networks and the target-based attention mechanism.