Search Results for author:
Found 7 papers, 0 papers with code
Embedding Lexical Features via Tensor Decomposition for Small Sample Humor Recognition
We propose a novel tensor embedding method that can effectively extract lexical features for humor recognition.
Recognizing Humour using Word Associations and Humour Anchor Extraction
This paper attempts to marry the interpretability of statistical machine learning approaches with the more robust models of joke structure and joke semantics capable of being learned by neural models.
Predicting Word Association Strengths
This paper looks at the task of predicting word association strengths across three datasets; WordNet Evocation (Boyd-Graber et al., 2006), University of Southern Florida Free Association norms (Nelson et al., 2004), and Edinburgh Associative Thesaurus (Kiss et al., 1973).
SRHR at SemEval-2017 Task 6: Word Associations for Humour Recognition
This paper explores the role of semantic relatedness features, such as word associations, in humour recognition.
Effects of Semantic Relatedness between Setups and Punchlines in Twitter Hashtag Games
This paper explores humour recognition for Twitter-based hashtag games.
