Constructing literature abstracts by computer: techniques and prospects
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
SCISOR: extracting information from on-line news
Communications of the ACM
Subtopic structuring for full-length document access
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A full-text retrieval system with a dynamic abstract generation function
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Automatic condensation of electronic publications by sentence selection
Information Processing and Management: an International Journal - Special issue: summarizing text
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Journal of the ACM (JACM)
Automatically summarising Web sites: is there a way around it?
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Generic summaries for indexing in information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
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Information Processing and Management: an International Journal
Automatic Text Summarization Using Unsupervised and Semi-supervised Learning
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Learning for Text Summarization Using Labeled and Unlabeled Sentences
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
The diversity-based approach to open-domain text summarization
Information Processing and Management: an International Journal
An automatic extraction of key paragraphs based on context dependency
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Evaluation of importance of sentences based on connectivity to title
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Toward the "at-a-glance" summary: phrase-representation summarization method
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
CAST: a computer-aided summarisation tool
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Extracting important sentences with support vector machines
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Supervised ranking in open-domain text summarization
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Extracting key paragraph based on topic and event detection: towards multi-document summarization
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
Evaluation of phrase-representation summarization based on information retrieval task
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
Combining optimal clustering and Hidden Markov models for extractive summarization
MultiSumQA '03 Proceedings of the ACL 2003 workshop on Multilingual summarization and question answering - Volume 12
An evolutionary approach for improving the quality of automatic summaries
MultiSumQA '03 Proceedings of the ACL 2003 workshop on Multilingual summarization and question answering - Volume 12
Examining the consensus between human summaries: initial experiments with factoid analysis
HLT-NAACL-DUC '03 Proceedings of the HLT-NAACL 03 on Text summarization workshop - Volume 5
A system for query-specific document summarization
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Corpus and evaluation measures for multiple document summarization with multiple sources
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Using gene expression programming to construct sentence ranking functions for text summarization
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Pseudo-relevance feedback and statistical query expansion for web snippet generation
Information Processing Letters
Adaptive Web SitesA Knowledge Extraction from Web Data Approach
Proceedings of the 2008 conference on Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
Extracting key paragraph based on topic and event detection: towards multi-document summarization
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
Evaluation of phrase-representation summarization based on information retrieval task
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Corpus-based Chinese-Korean abstracting translation system
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Improving XML search by generating and utilizing informative result snippets
ACM Transactions on Database Systems (TODS)
Constructing query-biased summaries: a comparison of human and system generated snippets
Proceedings of the third symposium on Information interaction in context
Automatic text summarization based on word-clusters and ranking algorithms
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Automatic text summarization using two-step sentence extraction
AIRS'04 Proceedings of the 2004 international conference on Asian Information Retrieval Technology
Why read if you can skim: towards enabling faster screen reading
Proceedings of the International Cross-Disciplinary Conference on Web Accessibility
Information Processing and Management: an International Journal
Accessible skimming: faster screen reading of web pages
Proceedings of the 25th annual ACM symposium on User interface software and technology
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This paper describes a system for generating text abstracts which relies on a general, purely statistical principle, i.e., on the notion of "relevance", as it is defined in terms of the combination of feild weights of words in a sentence. The system generates abstracts from newspaper articles by selecting the "most relevant" sentences and combining them in text order. Since neither domain knowledge nor text-sort-specific heuristics are involved, this system provides maximal generality and flexibility. Also, it is fast and can be efficiently implemented for both on-line and off-line purposes. An experiment shows that recall and precision for the extracted sentences (taking the sentences extracted by human subjects as a baseline) is within the same range as recall/precision when the human subjects are compared amongst each other: this means in fact that the performance of the system is indistinguishable from the performance of a human abstractor. Finally, the system yields significantly better results than a default "lead" algorithm does which chooses just some initial sentences from the text.