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
Using Justification Patterns to Advise Novice UNIX Users
Artificial Intelligence Review - Special issue on intelligent help systems for Unix part III: natural language dialogue
An Integrated Approach for Generating Arguments and Rebuttals and Understanding Rejoinders
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
Collaborative response generation in planning dialogues
Computational Linguistics - Special issue on natural language generation
Response generation in collaborative negotiation
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
A Probabilistic Approach for Argument Interpretation
User Modeling and User-Adapted Interaction
Towards the generation of rebuttals in a Bayesian Argumentation System
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
Recognizing intentions from rejoinders in a Bayesian interactive argumentation system
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
| Hi-index | 0.00 |
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.