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UpdateNews: a news clustering and summarization system using efficient text processing

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International Conference on Digital Libraries archive
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries table of contents

Vancouver, BC, Canada

SESSION: Automatic classification table of contents

Pages: 438 - 439

Year of Publication: 2007

ISBN:978-1-59593-644-8

Authors

Takaharu Takeda	Graduate University for Advanced Studies, 2-1-2 Hitotsubashi, Chiyoda, Japan
Atsuhiro Takasu	National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda, Japan

Sponsors

ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

ACM New York, NY, USA

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ABSTRACT

This paper proposes a news articles clustering and summarization system. It provides integrated access to news articles from various news sites. The system consists of a crawler, topic detector, and summarizer. This paper describes its efficient summarization technique to handle large amounts of crawled news articles.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	James Allan, Topic Detection and Tracking: Event-Based Information Organization, Kluwer Academic Publishers, Norwell, MA, 2002
	2	K. R. McKeown, et al. Tracking and summarizing news on a daily basis with Columbia's Newsblaster. In Proc. the Human Language Technology Conference, 2002.