Machine Learning
The Theory and Practice of Discourse Parsing and Summarization
The Theory and Practice of Discourse Parsing and Summarization
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The rhetorical parsing of unrestricted texts: a surface-based approach
Computational Linguistics
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Robust discourse parsing via discourse markers, topicality and position
Natural Language Engineering
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Shallow parsing with conditional random fields
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
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
Head-Driven Statistical Models for Natural Language Parsing
Computational Linguistics
Representing Discourse Coherence: A Corpus-Based Study
Computational Linguistics
Speech and Language Processing (2nd Edition)
Speech and Language Processing (2nd Edition)
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Discourse chunking and its application to sentence compression
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
The Journal of Machine Learning Research
Evaluating discourse-based answer extraction for why-question answering
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Domain adaptation of natural language processing systems
Domain adaptation of natural language processing systems
An effective discourse parser that uses rich linguistic information
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American 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-level relations for opinion analysis
Discourse-level relations for opinion analysis
Machine Learning: A Probabilistic Perspective
Machine Learning: A Probabilistic Perspective
Exploiting discourse information to identify paraphrases
Expert Systems with Applications: An International Journal
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We propose a complete probabilistic discriminative framework for performing sentence-level discourse analysis. Our framework comprises a discourse segmenter, based on a binary classifier, and a discourse parser, which applies an optimal CKY-like parsing algorithm to probabilities inferred from a Dynamic Conditional Random Field. We show on two corpora that our approach outperforms the state-of-the-art, often by a wide margin.