Text generation: using discourse strategies and focus constraints to generate natural language text
Text generation: using discourse strategies and focus constraints to generate natural language text
Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
A maximum entropy approach to natural language processing
Computational Linguistics
The decomposition of human-written summary sentences
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Summarization beyond sentence extraction: a probabilistic approach to sentence compression
Artificial Intelligence
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
A noisy-channel model for document compression
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Probabilistic text structuring: experiments with sentence ordering
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Sentence Fusion for Multidocument News Summarization
Computational Linguistics
Induction of Word and Phrase Alignments for Automatic Document Summarization
Computational Linguistics
Towards developing generation algorithms for text-to-text applications
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
In-browser summarisation: generating elaborative summaries biased towards the reading context
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Focused and aggregated search: a perspective from natural language generation
Information Retrieval
Spanning tree approaches for statistical sentence generation
Empirical methods in natural language generation
Text specificity and impact on quality of news summaries
MTTG '11 Proceedings of the Workshop on Monolingual Text-To-Text Generation
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We examine the problem of content selection in statistical novel sentence generation. Our approach models the processes performed by professional editors when incorporating material from additional sentences to support some initially chosen key summary sentence, a process we refer to as Sentence Augmentation. We propose and evaluate a method called "Seed and Grow" for selecting such auxiliary information. Additionally, we argue that this can be performed using schemata, as represented by word-pair co-occurrences, and demonstrate its use in statistical summary sentence generation. Evaluation results are supportive, indicating that a schemata model significantly improves over the baseline.