Building natural language generation systems
Building natural language generation systems
Probabilistic text structuring: experiments with sentence ordering
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Assigning time-stamps to event-clauses
TASIP '01 Proceedings of the workshop on Temporal and spatial information processing - Volume 13
Inferring strategies for sentence ordering in multidocument news summarization
Journal of Artificial Intelligence Research
A machine learning approach to sentence ordering for multidocument summarization and its evaluation
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Evaluating centering for information ordering using corpora
Computational Linguistics
Domain-independent shallow sentence ordering
SRWS '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium
A bottom-up approach to sentence ordering for multi-document summarization
Information Processing and Management: an International Journal
Content modeling using latent permutations
Journal of Artificial Intelligence Research
A preference learning approach to sentence ordering for multi-document summarization
Information Sciences: an International Journal
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In this paper, we propose a sentence ordering algorithm using a semi-supervised sentence classification and historical ordering strategy. The classification is based on the manifold structure underlying sentences, addressing the problem of limited labeled data. The historical ordering helps to ensure topic continuity and avoid topic bias. Experiments demonstrate that the method is effective.