Attention, intentions, and the structure of discourse
Computational Linguistics
A predictive approach for the generation of rhetorical devices
Computational Intelligence
Getting the message across in RST-based text generation
Current research in natural language generation
A problem for RST: the need for multi-level discourse analysis
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
Empirical studies on the disambiguation of cue phrases
Computational Linguistics
Intention-based segmentation: human reliability and correlation with linguistic cues
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Multi-paragraph segmentation of expository text
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Toward a synthesis of two accounts of discourse structure
Computational Linguistics
Empirical studies in discourse
Computational Linguistics
Discourse segmentation by human and automated means
Computational Linguistics
User-system dialogues and the notion of focus
The Knowledge Engineering Review
Learning features that predict cue usage
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Expectations in incremental discourse processing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Language-specific mappings from semantics to syntax
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
A corpus-based analysis for the ordering of clause aggregation operators
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
SPoT: a trainable sentence planner
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Can nominal expressions achieve multiple goals?: an empirical study
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Learning attribute selections for non-pronominal expressions
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Anaphora and Discourse Structure
Computational Linguistics
Mining discourse markers for Chinese textual summarization
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
Building a discourse-tagged corpus in the framework of Rhetorical Structure Theory
SIGDIAL '01 Proceedings of the Second SIGdial Workshop on Discourse and Dialogue - Volume 16
Generating basic skills reports for low-skilled readers*
Natural Language Engineering
Mining discourse markers for Chinese textual summarization
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
Switching to real-time tasks in multi-tasking dialogue
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Annotation and data mining of the Penn Discourse TreeBank
DiscAnnotation '04 Proceedings of the 2004 ACL Workshop on Discourse Annotation
Cue phrase classification using machine learning
Journal of Artificial Intelligence Research
An empirical approach to temporal reference resolution
Journal of Artificial Intelligence Research
Towards personality-based user adaptation: psychologically informed stylistic language generation
User Modeling and User-Adapted Interaction
An investigation of interruptions and resumptions in multi-tasking dialogues
Computational Linguistics
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 cue selection and placement in order to devise strategies for automatic text generation. Much previous work in this area has relied on ad hoc methods. Our coding scheme for the exhaustive analysis of discourse allows a systematic evaluation and refinement of hypotheses concerning cues. We report two results based on this analysis: a comparison of the distribution of SINCE and BECAUSE in our corpus, and the impact of embeddedness on cue selection.