Attention, intentions, and the structure of discourse
Computational Linguistics
Planning for conjunctive goals
Artificial Intelligence
Formalizing planning knowledge for hierarchical planning
Computational Intelligence
Getting the message across in RST-based text generation
Current research in natural language generation
Artificial Intelligence
Communicative acts for explanation generation
International Journal of Man-Machine Studies
Explanation and interaction: the computer generation of explanatory dialogues
Explanation and interaction: the computer generation of explanatory dialogues
A problem for RST: the need for multi-level discourse analysis
Computational Linguistics
Recognizing complex discourse acts: a tripartite plan-based model of dialogue
Recognizing complex discourse acts: a tripartite plan-based model of dialogue
Planning English Sentences
Customizing RST for the Automatic Production of Technical Manuals
Proceedings of the 6th International Workshop on Natural Language Generation: Aspects of Automated Natural Language Generation
Employing Knowledge Resources in a New Text Planner Architecture
Proceedings of the 6th International Workshop on Natural Language Generation: Aspects of Automated Natural Language Generation
A structure for plans and behavior.
A structure for plans and behavior.
Planning text for advisory dialogues: capturing intentional and rhetorical information
Computational Linguistics
A tripartite plan-based model of dialogue
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
GEA: A Complete, Modular System for Generating Evaluative Arguments
ICCS '01 Proceedings of the International Conference on Computational Sciences-Part I
Generating and evaluating evaluative arguments
Artificial Intelligence
From local to global coherence: a bottom-up approach to text planning
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
| Hi-index | 0.00 |
Research in discourse processing has identified two representational requirements for discourse planning systems. First, discourse plans must adequately represent the intentional structure of the utterances they produce in order to enable a computational discourse agent to respond effectively to communicative failures [15]. Second, discourse plans must represent the informational structure of utterances. In addition to these representational requirements, we argue that discourse planners should be formally characterisable in terms of soundness and completeness.