Abstract
This chapter presents a visual text mining approach to modeling humor within text. It includes algorithms for visualizing and discovering shifts in text interpretation as intelligent agents parse meaning from garden path jokes. Three successful text visualization methods are described to identify discrimination features for humorous and non-humorous texts. These visualization methods include Collocated Paired Coordinates, Heat maps, and two-dimensional Boolean plots.
All intellectual labor is inherently humorous.
George Bernard Shaw
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Kovalerchuk, B. (2018). Visual Text Mining: Discovery of Incongruity in Humor Modeling. In: Visual Knowledge Discovery and Machine Learning. Intelligent Systems Reference Library, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-319-73040-0_9
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DOI: https://doi.org/10.1007/978-3-319-73040-0_9
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