Kleio: a knowledge-enriched information retrieval system for biology

Authors:
Chikashi Nobata;Philip Cotter;Naoaki Okazaki;Brian Rea;Yutaka Sasaki;Yoshimasa Tsuruoka;Jun'ichi Tsujii;Sophia Ananiadou
Affiliations:
The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm;The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm;The University of Tokyo, Tokyo, Japan;The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm;The University of Manchester, Manchester, United Kngdm;The University of Manchester, Manchester, United Kngdm;The University of Manchester / National Centre for Text Mining (NaCTeM, Manchester, United Kngdm and The University of Tokyo, Tokyo, Japan;The University of Manchester / National Centre for Text Mining (NaCTeM), Manchester, United Kngdm
Venue:
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2008

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Abstract

Kleio is an advanced information retrieval (IR) system developed at the UK National Centre for Text Mining (NaCTeM)1. The system offers textual and metadata searches across MEDLINE and provides enhanced searching functionality by leveraging terminology management technologies.