Modeling suppositions in users' arguments

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3538 LNAI, Issue , 2005, Pages 19-29

  George, Sarah ^a   Zukerman, Ingrid ^a   Niemann, Michael ^a  

^a MONASH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SCIENCE; COMPUTER SIMULATION; SPEECH COMMUNICATION; SPEECH RECOGNITION;

BAYESIAN INTERACTIVE ARGUMENTATION SYSTEM (BIAS); CONVERSATION; MIS COMMUNICATION; SUPPOSITIONS;

ARTIFICIAL INTELLIGENCE;

EID: 26944499371     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11527886_5     Document Type: Conference Paper

References (9)

1. Sarah George and Ingrid Zukerman. An anytime algorithm for interpreting arguments. In PRICAI2004 - Proceedings of the Eighth Pacific Rim International Conference on Artificial Intelligence, 311-321, Auckland, New Zealand, 2004.
2. John Gurney, Don Perils, and Khemdut Purang. Interpreting presuppositions using active logic: From contexts to utterances. Computational Intelligence, 13(3):391-413, 1997.
3. S. J. Kaplan. Cooperative responses from a portable natural language query system. Artificial Intelligence, 19:165-187, 1982.
4. Robert E. Mercer. Presuppositions and default reasoning: A study in lexical pragmatics. In J. Pustejovski and S. Bergler, editors, ACL SIG Workshop on Lexical Semantics and Knowledge Representation (SIGLEX), 321-339. 1991.
5. Amihai Motro. SEAVE: a mechanism for verifying user presuppositions in query systems. ACM Transactions on Information Systems (TOIS), 4(4):312-330, 1986.
6. Judea Pearl. Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann Publishers, San Mateo, California, 1988.
7. Ingrid Zukerman and Sarah George. A probabilistic approach for argument interpretation. User Modeling and User-Adapted Interaction, Special Issue on Language-Based Interaction, 2005.
8. Ingrid Zukerman, Sarah George, and Mark George. Incorporating a user model into an information theoretic framework for argument interpretation. In UM03 - Proceedings of the Ninth International Conference on User Modeling, 106-116, Johnstown, Pennsylvania, 2003.
9. Ingrid Zukerman, Michael Niemann, and Sarah George. Improving the presentation of argument interpretations based on user trials. In AI'04 - Proceedings of the 17th Australian Joint Conference on Artificial Intelligence, 587-598, Cairns, Australia, 2004.