The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Advances in Automatic Text Summarization
Advances in Automatic Text Summarization
Journal of Global Optimization
The diversity-based approach to open-domain text summarization
Information Processing and Management: an International Journal
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
A formal model for information selection in multi-sentence text extraction
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
CollabSum: exploiting multiple document clustering for collaborative single document summarizations
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Developing learning strategies for topic-based summarization
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Hierarchical summarization of large documents
Journal of the American Society for Information Science and Technology
GA, MR, FFNN, PNN and GMM based models for automatic text summarization
Computer Speech and Language
Integrating clustering and multi-document summarization to improve document understanding
Proceedings of the 17th ACM conference on Information and knowledge management
Biased LexRank: Passage retrieval using random walks with question-based priors
Information Processing and Management: an International Journal
Towards More Effective Text Summarization Based on Textual Association Networks
SKG '08 Proceedings of the 2008 Fourth International Conference on Semantics, Knowledge and Grid
Expert Systems with Applications: An International Journal
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
An exploration of document impact on graph-based multi-document summarization
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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
Document summarization using conditional random fields
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Text Mining on Semi-structured E-Government Digital Archives of China
WMWA '09 Proceedings of the 2009 Second Pacific-Asia Conference on Web Mining and Web-based Application
Text summarization model based on the budgeted median problem
Proceedings of the 18th ACM conference on Information and knowledge management
Multi-document summarization using sentence-based topic models
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Expert Systems with Applications: An International Journal
A study of global inference algorithms in multi-document summarization
ECIR'07 Proceedings of the 29th European conference on IR research
Modeling Document Summarization as Multi-objective Optimization
IITSI '10 Proceedings of the 2010 Third International Symposium on Intelligent Information Technology and Security Informatics
iRANK: A rank-learn-combine framework for unsupervised ensemble ranking
Journal of the American Society for Information Science and Technology
A hybrid hierarchical model for multi-document summarization
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Generic Text Summarization for Turkish
The Computer Journal
Differential evolution algorithm with ensemble of parameters and mutation strategies
Applied Soft Computing
Applying regression models to query-focused multi-document summarization
Information Processing and Management: an International Journal
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
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Extractive multidocument summarization is modeled as a modified p-median problem. The problem is formulated with taking into account four basic requirements, namely, relevance, information coverage, diversity, and length limit that should satisfy summaries. To solve the optimization problem a self-adaptive differential evolution algorithm is created. Differential evolution has been proven to be an efficient and robust algorithm for many real optimization problems. However, it still may converge toward local optimum solutions, need to manually adjust the parameters, and finding the best values for the control parameters is a consuming task. In the paper is proposed a self-adaptive scaling factor in original DE to increase the exploration and exploitation ability. This paper has found that self-adaptive differential evolution can efficiently find the best solution in comparison with the canonical differential evolution. We implemented our model on multi-document summarization task. Experiments have shown that the proposed model is competitive on the DUC2006 dataset.