Humor Recognition Based on Dynamic Commonsense Reasoning and Multi-Dimension Semantic Features
As an emerging topic in NLP,humor recognition is to discriminate whether a given text expresses humor.To fully capture emotional features within the text,we propose CMSOR method based on dynamic commonsense reasoning and multi-dimension semantic features.It adopts the commonsense to infer latent emotion feature of speakers from the text,then leverages WordNet lexicon to calculate word level distances as the inconsistent features and the ambiguous features.We make use of these three humor-specific features to construct humor semantics.Ex-periments on three publicly available benchmarks demonstrate that CMSOR is superior to state-of-the-art models.