Generating and evaluating evaluative arguments
TL;DR: An evaluation framework in which the effectiveness of evaluative arguments can be measured with real users is devised and implemented, and two basic hypotheses on which the design of the computational model is based are tested.
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About: This article is published in Artificial Intelligence. The article was published on 01 Aug 2006. and is currently open access. The article focuses on the topics: Argument & Selection (linguistics).
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Citations
Argumentation in artificial intelligence
TL;DR: A number of foundational contributions provided the basis for the formulation of argumentation models and their promotion in AI related settings and then a number of new themes that have emerged in recent years are considered, many of which provide the principal topics of the research presented in this volume.
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Survey of the state of the art in natural language generation: core tasks, applications and evaluation
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TL;DR: A survey of the state of the art in natural language generation can be found in this article, with an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organized.
A review of natural language processing techniques for opinion mining systems
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Using arguments for making and explaining decisions
Leila Amgoud,Henri Prade +1 more
TL;DR: This paper articulates the optimistic and pessimistic decision criteria defined in qualitative decision making under uncertainty, in terms of an argumentation process.
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A systematic review and taxonomy of explanations in decision support and recommender systems
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TL;DR: This work systematically review the literature on explanations in advice-giving systems, which includes recommender systems, and derives a novel comprehensive taxonomy of aspects to be considered when designing explanation facilities for current and future decision support systems.
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