Towards a computational account of persuasion in law
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Automatic detection of arguments in legal texts
Proceedings of the 11th international conference on Artificial intelligence and law
The Carneades model of argument and burden of proof
Artificial Intelligence
Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases
Proceedings of the 2007 conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference
Similarity, precedent and argument from analogy
Artificial Intelligence and Law
Artificial Intelligence and Law
Classifying arguments by scheme
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Review: representing and classifying arguments on the semantic web
The Knowledge Engineering Review
Approaches to text mining arguments from legal cases
Semantic Processing of Legal Texts
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This paper surveys the state-of-the-art of argumentation schemes used as argument extraction techniques in cognitive informatics and uses examples to show how a series of connected problems needs to be solved to move these techniques forward to computational implementation. Some of the schemes considered are argument from expert opinion, practical reasoning, argument from negative consequences, fear appeal arguments, argument from commitment, argument from inconsistent commitments, and the circumstantial ad hominem argument. The paper shows how schemes need to be formed into clusters of sub-schemes work toward a classification system of schemes from the bottom up, and how identification conditions for each scheme can be helpful for argument extraction.