A new approach to unsupervised text summarization
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Algorithmics for Hard Problems
Algorithmics for Hard Problems
Kernel methods for relation extraction
The Journal of Machine Learning Research
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
A formal model for information selection in multi-sentence text extraction
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Text summarization model based on maximum coverage problem and its variant
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
A study of global inference algorithms in multi-document summarization
ECIR'07 Proceedings of the 29th European conference on IR research
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Applied Computational Intelligence and Soft Computing
Multi-document summarization exploiting frequent itemsets
Proceedings of the 27th Annual ACM Symposium on Applied Computing
MCMR: Maximum coverage and minimum redundant text summarization model
Expert Systems with Applications: An International Journal
GenDocSum+MCLR: Generic document summarization based on maximum coverage and less redundancy
Expert Systems with Applications: An International Journal
Multiple documents summarization based on evolutionary optimization algorithm
Expert Systems with Applications: An International Journal
Text summarization while maximizing multiple objectives with lagrangian relaxation
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Multi-document summarization based on the Yago ontology
Expert Systems with Applications: An International Journal
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We propose a multi-document generic summarization model based on the budgeted median problem. Our model selects sentences to generate a summary so that every sentence in the document cluster can be assigned to and be represented by a sentence in the summary as much as possible. The advantage of this model is that it covers the entire relevant part of the document cluster through sentence assignment and can incorporate asymmetric relations between sentences such as textual entailment.