Kleio: a knowledge-enriched information retrieval system for biology

doi:10.1145/1390334.1390504

Kleio: a knowledge-enriched information retrieval system for biology

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Authors:	Chikashi Nobata	The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm
	Philip Cotter	The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm
	Naoaki Okazaki	The University of Tokyo, Tokyo, Japan
	Brian Rea	The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm
	Yutaka Sasaki	The University of Manchester, Manchester, United Kngdm
	Yoshimasa Tsuruoka	The University of Manchester, Manchester, United Kngdm
	Jun'ichi Tsujii	The University of Manchester / National Centre for Text Mining (NaCTeM, Manchester, United Kngdm and The University of Tokyo, Tokyo, Japan
	Sophia Ananiadou	The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm

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	· Proceeding
	SIGIR '08 Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
	Pages 787-788 ACM New York, NY, USA ©2008 table of contents ISBN: 978-1-60558-164-4 doi>10.1145/1390334.1390504

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Tags: design information retrieval medical information systems medline named entity recognition

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