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
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Minimizing word error rate in textual summaries of spoken language
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
Information Processing and Management: an International Journal
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Graph-based keyword extraction for single-document summarization
MMIES '08 Proceedings of the Workshop on Multi-source Multilingual Information Extraction and Summarization
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
PageRank for ranking authors in co-citation networks
Journal of the American Society for Information Science and Technology
A comprehensive comparative evaluation of RST-based summarization methods
ACM Transactions on Speech and Language Processing (TSLP)
Subject metadata support powered by Maui
Proceedings of the 10th annual joint conference on Digital libraries
EUSUM: extracting easy-to-understand english summaries for non-native readers
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
PageRank without hyperlinks: Structural reranking using links induced by language models
ACM Transactions on Information Systems (TOIS)
Quantifying the limits and success of extractive summarization systems across domains
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Extractive speech summarization using shallow rhetorical structure modeling
IEEE Transactions on Audio, Speech, and Language Processing
Conundrums in unsupervised keyphrase extraction: making sense of the state-of-the-art
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
PageRank: standing on the shoulders of giants
Communications of the ACM
Revisiting centrality-as-relevance: support sets and similarity as geometric proximity
Journal of Artificial Intelligence Research
Temporal corpus summarization using submodular word coverage
Proceedings of the 21st ACM international conference on Information and knowledge management
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In general, centrality-based retrieval models treat all elements of the retrieval space equally, which may reduce their effectiveness. In the specific context of extractive summarization (or important passage retrieval), this means that these models do not take into account that information sources often contain lateral issues, which are hardly as important as the description of the main topic, or are composed by mixtures of topics. We present a new two-stage method that starts by extracting a collection of key phrases that will be used to help centrality-as-relevance retrieval model. We explore several approaches to the integration of the key phrases in the centrality model. The proposed method is evaluated using different datasets that vary in noise (noisy vs clean) and language (Portuguese vs English). Results show that the best variant achieves relative performance improvements of about 31% in clean data and 18% in noisy data.