Mining Biomedical Entity from Literature Based on CRF

DOI

10.2991/nceece-15.2016.255How to use a DOI?

Keywords

biomedical entity recognition; CRF; Feature selection; text mining

Abstract

With the rapid expansion of biomedical literatures, it provides an opportunity for mining biomedical knowledge from the huge amount of biomedical text. Entity recognition is a challenging task of biomedical text mining. In this work, we described a method to identify biomedical entity based on Conditional Random Fields(CRF). In the test dataset, the performance of the submitted method obtained the relatively satisfied performance . At the same time, we also develop a system with identified six class entities using different color representation Taken together, our method is promising for developing the technology of biomedical entity recognition.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lejun Gong
AU  - Ronggen Yang
AU  - Jiacheng Feng
AU  - Geng Yang
PY  - 2015/12
DA  - 2015/12
TI  - Mining Biomedical Entity from Literature Based on CRF
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 1436
EP  - 1439
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.255
DO  - 10.2991/nceece-15.2016.255
ID  - Gong2015/12
ER  -