Hybrid context enriched deep learning model for fine-grained sentiment analysis in textual and visual semiotic modality social data
Detecting sentiments in natural language is tricky even for humans, making its automated
detection more complicated. This research proffers a hybrid deep learning model for fine-
grained sentiment prediction in real-time multimodal data. It reinforces the strengths of deep
learning nets in combination to machine learning to deal with two specific semiotic systems,
namely the textual (written text) and visual (still images) and their combination within the
online content using decision level multimodal fusion. The proposed contextual ConvNet …
detection more complicated. This research proffers a hybrid deep learning model for fine-
grained sentiment prediction in real-time multimodal data. It reinforces the strengths of deep
learning nets in combination to machine learning to deal with two specific semiotic systems,
namely the textual (written text) and visual (still images) and their combination within the
online content using decision level multimodal fusion. The proposed contextual ConvNet …
以上显示的是最相近的搜索结果。 查看全部搜索结果