Approximation algorithms for NP-hard problems
Using hidden Markov modeling to decompose human-written summaries
Computational Linguistics - Summarization
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
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Learning non-isomorphic tree mappings for machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
A formal model for information selection in multi-sentence text extraction
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Multi-document summarization by sentence extraction
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
Sentence compression beyond word deletion
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Summarization with a joint model for sentence extraction and compression
ILP '09 Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing
A scalable global model for summarization
ILP '09 Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing
Global inference for sentence compression an integer linear programming approach
Journal of Artificial Intelligence Research
Sentence compression as tree transduction
Journal of Artificial Intelligence Research
Quasi-synchronous grammars: alignment by soft projection of syntactic dependencies
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
A study of global inference algorithms in multi-document summarization
ECIR'07 Proceedings of the 29th European conference on IR research
Automatic generation of story highlights
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Title generation with quasi-synchronous grammar
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Exploiting separability in large-scale linear support vector machine training
Computational Optimization and Applications
Jointly learning to extract and compress
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
TopicDSDR: combining topic decomposition and data reconstruction for summarization
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
PPSGen: learning to generate presentation slides for academic papers
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Multi-document summarization involves many aspects of content selection and surface realization. The summaries must be informative, succinct, grammatical, and obey stylistic writing conventions. We present a method where such individual aspects are learned separately from data (without any hand-engineering) but optimized jointly using an integer linear programme. The ILP framework allows us to combine the decisions of the expert learners and to select and rewrite source content through a mixture of objective setting, soft and hard constraints. Experimental results on the TAC-08 data set show that our model achieves state-of-the-art performance using ROUGE and significantly improves the informativeness of the summaries.