tailieunhanh - Báo cáo khoa học: "Humor as Circuits in Semantic Networks"

This work presents a first step to a general implementation of the Semantic-Script Theory of Humor (SSTH). Of the scarce amount of research in computational humor, no research had focused on humor generation beyond simple puns and punning riddles. We propose an algorithm for mining simple humorous scripts from a semantic network (ConceptNet) by specifically searching for dual scripts that jointly maximize overlap and incongruity metrics in line with Raskin’s Semantic-Script Theory of Humor. . | Humor as Circuits in Semantic Networks Igor Labutov Cornell University iil4@ Hod Lipson Cornell University Abstract This work presents a first step to a general implementation of the Semantic-Script Theory of Humor SSTH . Of the scarce amount of research in computational humor no research had focused on humor generation beyond simple puns and punning riddles. We propose an algorithm for mining simple humorous scripts from a semantic network Concept-Net by specifically searching for dual scripts that jointly maximize overlap and incongruity metrics in line with Raskin s Semantic-Script Theory of Humor. Initial results show that a more relaxed constraint of this form is capable of generating humor of deeper semantic content than wordplay riddles. We evaluate the said metrics through a user-assessed quality of the generated two-liners. 1 Introduction While of significant interest in linguistics and philosophy humor had received less attention in the computational domain. And of that work most recent is predominately focused on humor recognition. See Ritchie 2001 for a good review. In this paper we focus on the problem of humor generation. While humor sarcasm recognition merits direct application to the areas such as information retrieval Friedland and Allan 2008 sentiment classification Mihalcea and Strapparava 2006 and humancomputer interaction Nijholt et al. 2003 the application of humor generation is not any less significant. First a good generative model of humor has the potential to outperform current discriminative models for humor recognition. Thus ability to Figure 1 Semantic circuit generate humor will potentially lead to better humor detection. Second a computational model that conforms to the verbal theory of humor is an accessible avenue for verifying the psycholinguistic theory. In this paper we take the Semantic Script Theory of Humor SSTH Attardo and Raskin 1991 - a widely accepted theory of verbal humor and build a .

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