Computational Humor

Abstract

In an effort to focus on tractable problems, computational natural language understanding systems have typically addressed language phenomena that are amenable to combinatorial approaches using static and stereotypical semantic representations. Although such approaches are adequate for much of language, they're not easily extended to capture humans' more creative language interpretation capacities. This paper proposes a model of humor comprehension based on frame-shifting within a simulation-based natural-language-understanding system.