Inferring domain plans in question-answering
Inferring domain plans in question-answering
Analyzing the structure of argumentative discourse
Computational Linguistics
Modeling the user's plans and goals
Computational Linguistics - Special issue on user modeling
Recognizing and responding to plan-oriented misconceptions
Computational Linguistics - Special issue on user modeling
Reasoning on a highlighted user model to respond to misconceptions
Computational Linguistics - Special issue on user modeling
The correction machine: a computer model of recognizing and producing belief justifications in argumentative dialogs
Understanding Editorial Text: A Computer Model of Argument Comprehension
Understanding Editorial Text: A Computer Model of Argument Comprehension
In-Depth Understanding: A Computer Model of Integrated Processing for Narrative Comprehension
In-Depth Understanding: A Computer Model of Integrated Processing for Narrative Comprehension
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In discourse processing, two major problems are understanding the underlying connections between successive dialog utterances and deciding on the content of a coherent dialog response. This paper presents a computational model of these tasks for a restricted class of argumentative dialogs. In these dialogs, each response presents a belief that justifies or contradicts another belief presented or inferred earlier in the dialog. Understanding a response involves relating a stated belief to these earlier beliefs, and producing a response involves selecting a belief to justify and deciding upon the set of beliefs to provide as its justification. Our approach is knowledge based, using general, common-sense justification rules to recognize how a belief is being justified and to form new justifications for beliefs. This approach provides the ability to recognise and respond to never before seen belief justifications, a necessary capability for any system that participates in dialogs involving disagreements.