Automated discourse generation using discourse structure relations
Artificial Intelligence - Special volume on natural language processing
Generating presentation constraints from rhetorical structure
HYPERTEXT '00 Proceedings of the eleventh ACM on Hypertext and hypermedia
The Theory and Practice of Discourse Parsing and Summarization
The Theory and Practice of Discourse Parsing and Summarization
D-LTAG System: Discourse Parsing with a Lexicalized Tree-Adjoining Grammar
Journal of Logic, Language and Information
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COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
Sentence level discourse parsing using syntactic and lexical information
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
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
A study to improve the efficiency of a discourse parsing system
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Using automatically labelled examples to classify rhetorical relations: An assessment
Natural Language Engineering
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EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
A novel discourse parser based on support vector machine classification
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Discourse segmentation of german written texts
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Text-level discourse parsing with rich linguistic features
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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This paper presents a system for automatically generating discourse structures from written text. The system is divided into two levels: sentence-level and text-level. The sentence-level discourse parser uses syntactic information and cue phrases to segment sentences into elementary discourse units and to generate discourse structures of sentences. At the text-level, constraints about textual adjacency and textual organization are integrated in a beam search in order to generate best discourse structures. The experiments were done with documents from the RST Discourse Treebank. It shows promising results in a reasonable search space compared to the discourse trees generated by human analysts.