Towards multidocument summarization by reformulation: progress and prospects
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iNeATS: interactive multi-document summarization
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Bayesian query-focused summarization
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An information-theoretic approach to automatic evaluation of summaries
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Satisfying information needs with multi-document summaries
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Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
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Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
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Bayesian unsupervised topic segmentation
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Improved affinity graph based multi-document summarization
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A study of global inference algorithms in multi-document summarization
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Automatic evaluation of topic coherence
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Unsupervised modeling of Twitter conversations
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Generating templates of entity summaries with an entity-aspect model and pattern mining
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
A hybrid hierarchical model for multi-document summarization
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Non-expert evaluation of summarization systems is risky
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
Summarizing contrastive viewpoints in opinionated text
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Topic aspect analysis for multi-document summarization
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
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COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts of ACL 2011
Discovery of topically coherent sentences for extractive summarization
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A class of submodular functions for document summarization
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Automatic labelling of topic models
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Automatic assessment of coverage quality in intelligence reports
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Probabilistic document modeling for syntax removal in text summarization
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Extractive multi-document summaries should explicitly not contain document-specific content
WASDGML '11 Proceedings of the Workshop on Automatic Summarization for Different Genres, Media, and Languages
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Generating aspect-oriented multi-document summarization with event-aspect model
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Toward a Unified Framework for Standard and Update Multi-Document Summarization
ACM Transactions on Asian Language Information Processing (TALIP)
Applied Computational Intelligence and Soft Computing
MCMR: Maximum coverage and minimum redundant text summarization model
Expert Systems with Applications: An International Journal
Personalized resource categorisation in folksonomies
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DualSum: a topic-model based approach for update summarization
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Apples to oranges: evaluating image annotations from natural language processing systems
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Applied Intelligence
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TopicDSDR: combining topic decomposition and data reconstruction for summarization
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
The effectiveness of automatic text summarization in mobile learning contexts
Computers & Education
Journal of Information Science
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We present an exploration of generative probabilistic models for multi-document summarization. Beginning with a simple word frequency based model (Nenkova and Vanderwende, 2005), we construct a sequence of models each injecting more structure into the representation of document set content and exhibiting ROUGE gains along the way. Our final model, HierSum, utilizes a hierarchical LDA-style model (Blei et al., 2004) to represent content specificity as a hierarchy of topic vocabulary distributions. At the task of producing generic DUC-style summaries, HierSum yields state-of-the-art ROUGE performance and in pairwise user evaluation strongly outperforms Toutanova et al. (2007)'s state-of-the-art discriminative system. We also explore HierSum's capacity to produce multiple 'topical summaries' in order to facilitate content discovery and navigation.