On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
Computational Linguistics
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Characterising measures of lexical distributional similarity
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatic identification of pro and con reasons in online reviews
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Just how mad are you? finding strong and weak opinion clauses
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning with compositional semantics as structural inference for subsentential sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Joint parsing and named entity recognition
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Exploring content models for multi-document summarization
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Learning document-level semantic properties from free-text annotations
Journal of Artificial Intelligence Research
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
Fast consensus decoding over translation forests
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
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Content modeling using latent permutations
Journal of Artificial Intelligence Research
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Semi-supervised latent variable models for sentence-level sentiment analysis
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Sentiment classification based on supervised latent n-gram analysis
Proceedings of the 20th ACM international conference on Information and knowledge management
Named entity recognition in tweets: an experimental study
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Automatic aggregation by joint modeling of aspects and values
Journal of Artificial Intelligence Research
| Hi-index | 0.00 |
In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the linguistic intuition that rich contextual information should be useful in these tasks. We present a framework which combines a supervised text analysis application with the induction of latent content structure. Both of these elements are learned jointly using the EM algorithm. The induced content structure is learned from a large unannotated corpus and biased by the underlying text analysis task. We demonstrate that exploiting content structure yields significant improvements over approaches that rely only on local context.