An Investigation into Computational Recognition of Children’s Jokes

Julia M. Taylor, Lawrence J. Mazlack

This paper presents an overview of a model for computational recognition of two-sentence-long jokes that are based on phonological similarity of words. The model takes into account orthographic, phonological and semantic representation of words. The joke recognition is based on knowledge that is provided by an ontology. The ontology is created by using entries from a children’s dictionary. Each noun in the dictionary is an instance of a concept in a concept hierarchy. An instance belongs to each concept to a certain degree. The concept hierarchy is modeled from WordNet. Semantic relationships between concepts are added from a collection of children’s texts and definitions in a children’s dictionary. Any two-sentence-long text is considered a joke if it contains two scripts that both overlap and oppose; and if there is a pair of similar sounding words (w1, w2), in which w1 is an instance of a concept of one script, and w2 is an instance of a concept of another.

Subjects: 13. Natural Language Processing; 11.2 Ontologies

Submitted: Apr 10, 2007


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