Extended person-machine interface
Artificial Intelligence
Text generation: using discourse strategies and focus constraints to generate natural language text
Text generation: using discourse strategies and focus constraints to generate natural language text
Attention, intentions, and the structure of discourse
Computational Linguistics
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Getting the message across in RST-based text generation
Current research in natural language generation
C4.5: programs for machine learning
C4.5: programs for machine learning
Emergent linguistic rules from inducing decision trees: disambiguating discourse clue words
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Expressing rhetorical relations in instructional text: a case study of the purpose relation
Computational Linguistics
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
A computational theory of the function of clue words in argument understanding
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Functional unification grammar revisited
ACL '87 Proceedings of the 25th annual meeting on Association for Computational Linguistics
Investigating cue selection and placement in tutorial discourse
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Cue phrase classification using machine learning
Journal of Artificial Intelligence Research
An Empirical Approach to Discourse Markers by Clustering
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
The rhetorical parsing of unrestricted texts: a surface-based approach
Computational Linguistics
Introduction to the special issue on natural language generation
Computational Linguistics - Special issue on natural language generation
Dialogue act tagging with Transformation-Based Learning
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
DiMLex: a lexicon of discourse markers for text generation and understanding
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Centering: A Parametric Theory and Its Instantiations
Computational Linguistics
An experiment to evaluate the effectiveness of cross-media cues in computer media
SIGDIAL '02 Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2
Generating and evaluating evaluative arguments
Artificial Intelligence
Acquiring the meaning of discourse markers
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Natural language generation for sponsored-search advertisements
Proceedings of the 9th ACM conference on Electronic commerce
Generating basic skills reports for low-skilled readers*
Natural Language Engineering
Annotation and data mining of the Penn Discourse TreeBank
DiscAnnotation '04 Proceedings of the 2004 ACL Workshop on Discourse Annotation
Learning content selection rules for generating object descriptions in dialogue
Journal of Artificial Intelligence Research
Individual and domain adaptation in sentence planning for dialogue
Journal of Artificial Intelligence Research
Generating and evaluating evaluative arguments
Artificial Intelligence
Evaluating automatic extraction of rules for sentence plan construction
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Towards personality-based user adaptation: psychologically informed stylistic language generation
User Modeling and User-Adapted Interaction
How can you say such things?!?: recognizing disagreement in informal political argument
LSM '11 Proceedings of the Workshop on Languages in Social Media
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Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanations. Previous attempts to devise rules for text generation were based on intuition or small numbers of constructed examples. We apply a machine learning program, C4.5, to induce decision trees for cue occurrence and placement from a corpus of data coded for a variety of features previously thought to affect cue usage. Our experiments enable us to identify the features with most predictive power, and show that machine learning can be used to induce decision trees useful for text generation.