C4.5: programs for machine learning
C4.5: programs for machine learning
A program for aligning sentences in bilingual corpora
Computational Linguistics - Special issue on using large corpora: I
Learning parse and translation decisions from examples with rich context
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
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Automatic detection of discourse structure by checking surface information in sentences
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
A decision-based approach to rhetorical parsing
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Evaluation in the ARPA machine translation program: 1993 methodology
HLT '94 Proceedings of the workshop on Human Language Technology
Summarization beyond sentence extraction: a probabilistic approach to sentence compression
Artificial Intelligence
The rhetorical parsing of unrestricted texts: a surface-based approach
Computational Linguistics
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
An empirical study in multilingual natural language generation: what should a text planner do?
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
Can text structure be incompatible with rhetorical structure?
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
Active learning with multiple views
Journal of Artificial Intelligence Research
A comprehensive comparative evaluation of RST-based summarization methods
ACM Transactions on Speech and Language Processing (TSLP)
Discourse segmentation for Spanish based on shallow parsing
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
DiSeg 1.0: The first system for Spanish discourse segmentation
Expert Systems with Applications: An International Journal
Discourse structure and language technology
Natural Language Engineering
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We empirically show that there are significant differences between the discourse structure of Japanese texts and the discourse structure of their corresponding English translations. To improve translation quality, we propose a computational model for rewriting discourse structures. When we train our model on a parallel corpus of manually built Japanese and English discourse structure trees, we learn to rewrite Japanese trees as trees that are closer to the natural English rendering than the original ones.