C4.5: programs for machine learning
C4.5: programs for machine learning
BankXX: a program to generate argument through case-base research
ICAIL '93 Proceedings of the 4th international conference on Artificial intelligence and law
Neural networks and open texture
ICAIL '93 Proceedings of the 4th international conference on Artificial intelligence and law
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Machine Learning
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Agent Dialogues with Conflicting Preferences
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
Teaching case-based argumentation through a model and examples
Teaching case-based argumentation through a model and examples
Tree Structures for Mining Association Rules
Data Mining and Knowledge Discovery
Flexible Agent Dialogue Strategies and Societal Communication Protocols
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Perceptrons: An Introduction to Computational Geometry
Perceptrons: An Introduction to Computational Geometry
Obtaining Best Parameter Values for Accurate Classification
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Formal systems for persuasion dialogue
The Knowledge Engineering Review
AGATHA: using heuristic search to automate the construction of case law theories
Artificial Intelligence and Law - Argumentation in artificial intelligence and law
Argument based machine learning applied to law
Artificial Intelligence and Law - Argumentation in artificial intelligence and law
Legal case-based reasoning as practical reasoning
Artificial Intelligence and Law - Argumentation in artificial intelligence and law
Data Structure for Association Rule Mining: T-Trees and P-Trees
IEEE Transactions on Knowledge and Data Engineering
A formal general setting for dialogue protocols
AIMSA'06 Proceedings of the 12th international conference on Artificial Intelligence: methodology, Systems, and Applications
Threshold tuning for improved classification association rule mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Facilitating case comparison using value judgments and intermediate legal concepts
Proceedings of the 13th International Conference on Artificial Intelligence and Law
Empirical argumentation: integrating induction and argumentation in MAS
ArgMAS'10 Proceedings of the 7th international conference on Argumentation in Multi-Agent Systems
A defeasible reasoning model of inductive concept learning from examples and communication
Artificial Intelligence
Argue to agree: A case-based argumentation approach
International Journal of Approximate Reasoning
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We describe PADUA, a protocol designed to support two agents debating a classification by offering arguments based on association rules mined from individual datasets. We motivate the style of argumentation supported by PADUA, and describe the protocol. We discuss the strategies and tactics that can be employed by agents participating in a PADUA dialogue. PADUA is applied to a typical problem in the classification of routine claims for a hypothetical welfare benefit. We particularly address the problems that arise from the extensive number of misclassified examples typically found in such domains, where the high error rate is a widely recognised problem. We give examples of the use of PADUA in this domain, and explore in particular the effect of intermediate predicates. We have also done a large scale evaluation designed to test the effectiveness of using PADUA to detect misclassified examples, and to provide a comparison with other classification systems.