Metaphor comprehension: A computational theory

By Walter Kintsch. Psychonomic Bulletin & Review, 2000

374 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/980dc6d3b7dfb6ffc5e638316b11eb201129a672

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In Artificial Intelligence

In Experimental and Cognitive Psychology

Citations in the corpus

Metaphor Comprehension: What Makes a Metaphor Difficult to Understand? (2002, methodology): “Kintsch (2000) has shown that this predication algorithm yields interpretations of simple Noun-is-a-Noun metaphors that are in agreement with our intuitions about the meaning of metaphors by comparing the vector generated by the model with appropriate landmarks.”
Domain and Function: A Dual-Space Model of Semantic Relations and Compositions (2012, background): “Past work suggests that recognizing relations and compositions are closely connected tasks (Kintsch, 2000, 2001; Mangalath, Quesada, & Kintsch, 2004).”
Understanding Fluency and Originality: A latent variable perspective (2014, background): “…n ( t u l R A A A B B B B B Importantly, because LSA uses a large representative corpus, and derives latent relations among words or phrases, it is ble to approximate human raters on a variety of complex tasks including metaphor comprehension (Kintsch, 2000), and ssay scoring (Foltz et al., 2013).”
Language comprehension is both embodied and symbolic (2008, background): “LSA is able to ‘understand’ metaphors (Kintsch 2000), and can assist in problem solving (Quesada et al. 2002).”
Symbol Interdependency in Symbolic and Embodied Cognition (2011, methodology): “Keywords: Symbolic; Embodied; Amodal; Modal; Perceptual simulations; Symbol interdependency; LSA; Semantic knowledge”
Extracting semantic representations from word co-occurrence statistics: A computational study (2007, methodology): “This has included using LSA to model metaphor comprehension (Kintsch, 2000; Kintsch & Bowles, 2002); a model of children's semantic memory built from an LSA analysis of a child corpus (Denhière & Lemaire, 2004); application to grading student essays (Miller, 2003); application of different sources…”
An Improved Model of Semantic Similarity Based on Lexical Co-Occurrence (2005, methodology): “The HAL methodology has been used for such diverse applications as modeling contextual constraints in the parsing of ambiguous sentences (Burgess & Lund, 1997a), distinguishing semantic and associative word priming (Lund, Burgess, & Atchley, 1995; Lund, Burgess, & Audet, 1996), and modeling dissocia”