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
Generic text summarization using relevance measure and latent semantic analysis
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Advances in Automatic Text Summarization
Advances in Automatic Text Summarization
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
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
A formal model for information selection in multi-sentence text extraction
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Hierarchical summarization of large documents
Journal of the American Society for Information Science and Technology
Information Processing and Management: an International Journal
Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
GA, MR, FFNN, PNN and GMM based models for automatic text summarization
Computer Speech and Language
Personalized PageRank Based Multi-document Summarization
WSCS '08 Proceedings of the IEEE International Workshop on Semantic Computing and Systems
AdaSum: an adaptive model for summarization
Proceedings of the 17th ACM conference on Information and knowledge management
Automatic generic document summarization based on non-negative matrix factorization
Information Processing and Management: an International Journal
Using query expansion in graph-based approach for query-focused multi-document summarization
Information Processing and Management: an International Journal
Biased LexRank: Passage retrieval using random walks with question-based priors
Information Processing and Management: an International Journal
Expert Systems with Applications: An International Journal
Enhancing diversity, coverage and balance for summarization through structure learning
Proceedings of the 18th international conference on World wide web
A SVM-Based Ensemble Approach to Multi-Document Summarization
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
Incorporating prior knowledge into a transductive ranking algorithm for multi-document summarization
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
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
Document summarization using conditional random fields
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Graph-based multi-modality learning for topic-focused multi-document summarization
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Multi-document summarization using sentence-based topic models
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
A study of global inference algorithms in multi-document summarization
ECIR'07 Proceedings of the 29th European conference on IR research
Using topic themes for multi-document summarization
ACM Transactions on Information Systems (TOIS)
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
Fuzzy swarm diversity hybrid model for text summarization
Information Processing and Management: an International Journal
Social summarization in collaborative web search
Information Processing and Management: an International Journal
Multi-document Summarization Using Minimum Distortion
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Applying regression models to query-focused multi-document summarization
Information Processing and Management: an International Journal
Expert Systems with Applications: An International Journal
Integrating Document Clustering and Multidocument Summarization
ACM Transactions on Knowledge Discovery from Data (TKDD)
Weighted consensus multi-document summarization
Information Processing and Management: an International Journal
Mathematical and Computer Modelling: An International Journal
A behavioural mode research on user-focus summarization
Mathematical and Computer Modelling: An International Journal
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
Multi-document summarization based on the Yago ontology
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
PSG: a two-layer graph model for document summarization
Frontiers of Computer Science: Selected Publications from Chinese Universities
Hi-index | 12.05 |
This paper proposes a constraint-driven document summarization approach emphasizing the following two requirements: (1) diversity in summarization, which seeks to reduce redundancy among sentences in the summary and (2) sufficient coverage, which focuses on avoiding the loss of the document's main information when generating the summary. The constraint-driven document summarization models with tuning the constraint parameters can drive content coverage and diversity in a summary. The models are formulated as a quadratic integer programming (QIP) problem. To solve the QIP problem we used a discrete PSO algorithm. The models are implemented on multi-document summarization task. The comparative results showed that the proposed models outperform other methods on DUC2005 and DUC2007 datasets.