Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text summarization based on the Global Document Annotation
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Fast generation of abstracts from general domain text corpora by extracting relevant sentences
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
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
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
GIST-IT: summarizing email using linguistic knowledge and machine learning
HLTKM '01 Proceedings of the workshop on Human Language Technology and Knowledge Management - Volume 2001
Evaluation of phrase-representation summarization based on information retrieval task
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
Summary of FAQs from a topical forum based on the native composition structure
Expert Systems with Applications: An International Journal
Sentence compression learned by news headline for displaying in small device
AIRS'04 Proceedings of the 2004 international conference on Asian Information Retrieval Technology
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We have developed a summarization method that creates a summary suitable for the process of sifting information retrieval results. Unlike conventional methods that extract important sentences, this method constructs short phrases to reduce the burden of reading long sentences. We have developed a prototype summarization system for Japanese. Through a rather large-scale task-based experiment, the summary this system creates proved to be effective to sift IR results. This summarization method is also applicable to other languages such as English.