Exploiting ontologies for deep learning: a case for sentiment mining

Poster & Demo

We present a practical method for explaining deep learning- based text mining with ontology-based information. Our approach uses the recently proposed OntoSenticNet ontology for sentiment mining, and consists of a composite deep learning classifier for sentiment mining, en- dowed with an ontology-driven attention module. The attention module analyzes the attention the neural network pays to semantic labels as- signed to bigrams in input texts.


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