Exploring the use of linguistic features in domain and genre classification
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Automatic detection of text genre
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
Text genre detection using common word frequencies
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
An unsupervised approach to recognizing discourse relations
ACL '02 Proceedings of the 40th Annual Meeting on Association for 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
The form is the substance: classification of genres in text
HLTKM '01 Proceedings of the workshop on Human Language Technology and Knowledge Management - Volume 2001
Journal of the American Society for Information Science and Technology
User-based identification of Web genres
Journal of the American Society for Information Science and Technology
Using automatically labelled examples to classify rhetorical relations: An assessment
Natural Language Engineering
Discourse Connective Argument Identification with Connective Specific Rankers
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
Sequence models and ranking methods for discourse parsing
Sequence models and ranking methods for discourse parsing
Revisiting readability: a unified framework for predicting text quality
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Automatic sense prediction for implicit discourse relations in text
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
Sense annotation in the Penn discourse treebank
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Fine-grained genre classification using structural learning algorithms
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Effective measures of domain similarity for parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
An annotated corpus for the analysis of VP ellipsis
Language Resources and Evaluation
Sentence-level instance-weighting for graph-based and transition-based dependency parsing
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Cross-lingual genre classification
EACL '12 Proceedings of the Student Research Workshop at the 13th Conference of the European Chapter of the Association for Computational Linguistics
The use of granularity in rhetorical relation prediction
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Discourse structure and language technology
Natural Language Engineering
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Articles in the Penn TreeBank were identified as being reviews, summaries, letters to the editor, news reportage, corrections, wit and short verse, or quarterly profit reports. All but the latter three were then characterised in terms of features manually annotated in the Penn Discourse TreeBank --- discourse connectives and their senses. Summaries turned out to display very different discourse features than the other three genres. Letters also appeared to have some different features. The two main findings involve (1) differences between genres in the senses associated with intra-sentential discourse connectives, inter-sentential discourse connectives and inter-sentential discourse relations that are not lexically marked; and (2) differences within all four genres between the senses of discourse relations not lexically marked and those that are marked. The first finding means that genre should be made a factor in automated sense labelling of non-lexically marked discourse relations. The second means that lexically marked relations provide a poor model for automated sense labelling of relations that are not lexically marked.