Result 1 to 20 of 108 total
Peering inside peer review with Bayesian models. (English)
Biswas, Gautam (ed.) et al., Artificial intelligence in education. 15th international conference, AIED 2011, Auckland, New Zealand, June 28 ‒ July 2011. Berlin: Springer (ISBN 978-3-642-21868-2/pbk). Lecture Notes in Computer Science 6738. Lecture Notes in Artificial Intelligence, 90-97 (2011).
1
The third workshop on behaviour modelling ‒ foundations and applications. (English)
France, Robert B. (ed.) et al., Modelling foundations and applications. 7th European conference, ECMFA 2011, Birmingham, UK, June 6‒9, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-21469-1/pbk). Lecture Notes in Computer Science 6698, 381-382 (2011).
2
Peering inside peer review with Bayesian models (English)
AIED, 90-97 (2011).
3
Can temporal representation and reasoning make a difference in automated legal reasoning?: lessons from an AI-based ethical reasoner (English)
ICAIL, 229-238 (2011).
4
Facilitating case comparison using value judgments and intermediate legal concepts (English)
ICAIL, 161-170 (2011).
5
The 13th international conference on artificial intelligence and law, Proceedings of the conference, June 6-10, 2011, Pittsburgh, PA, USA (English)
ICAIL (2011).
6
Eliciting informative feedback in peer review: Importance of problem-specific scaffolding. (English)
Aleven, Vincent (ed.) et al., Intelligent tutoring systems. 10th international conference, ITS 2010, Pittsburgh, PA, USA, June 14‒18, 2010. Proceedings, Part I. Berlin: Springer (ISBN 978-3-642-13387-9/pbk). Lecture Notes in Computer Science 6094, 95-104 (2010).
7
Argumentation with value judgments - an example of hypothetical reasoning (English)
JURIX, 67-76 (2010).
8
Eliciting informative feedback in peer review: importance of problem-specific scaffolding (English)
Intelligent Tutoring Systems (1), 95-104 (2010).
9
CHI 2010 special interest group: creating prosocial media for children (English)
CHI Extended Abstracts, 3185-3188 (2010).
10
Teaching a process model of legal argument with hypotheticals. (English)
Artif. Intell. Law 17, No. 4, 321-370 (2009).
11
Automatically classifying case texts and predicting outcomes. (English)
Artif. Intell. Law 17, No. 2, 125-165 (2009).
12
Smartactions: Context-aware mobile phone shortcuts. (English)
Gross, Tom (ed.) et al., Human-computer interaction ‒ INTERACT 2009. 12th IFIP TC 13 international conference, Uppsala, Sweden, August 24‒28, 2009. Proceedings, Part I. Berlin: Springer (ISBN 978-3-642-03654-5/pbk). Lecture Notes in Computer Science 5726, 796-799 (2009).
13
Toward modeling and teaching legal case-based adaptation with expert examples. (English)
McGinty, Lorraine (ed.) et al., Case-based reasoning research and development. 8th international conference on case-based reasoning, ICCBR 2009 Seattle, WA, USA, July 20‒23, 2009. Proceedings. Berlin: Springer (ISBN 978-3-642-02997-4/pbk). Lecture Notes in Computer Science 5650. Lecture Notes in Artificial Intelligence, 45-59 (2009).
14
Concepts, structures, and goals: redefining ill-definedness (English)
I. J. Artificial Intelligence in Education 19, No. 3, 253-266 (2009).
15
Evaluating an intelligent tutoring system for making legal arguments with hypotheticals (English)
I. J. Artificial Intelligence in Education 19, No. 4, 401-424 (2009).
16
Argument diagramming and diagnostic reliability (English)
JURIX, 106-115 (2009).
17
Smartactions: context-aware mobile phone shortcuts (English)
INTERACT (1), 796-799 (2009).
18
Toward modeling and teaching legal case-based adaptation with expert examples (English)
ICCBR, 45-59 (2009).
19
Assessing argument diagrams in an ill-defined domain (English)
AIED, 590-592 (2009).
20
Result 1 to 20 of 108 total
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