CONDITIONAL RANDOM FIELDS FOR TERM EXTRACTION

Xing Zhang, Yan Song, Alex Chengyu Fang

2010

Abstract

In this paper, we describe how to construct a machine learning framework that utilizes syntactic information in extraction of biomedical terms. Conditional random fields (CRF), is used as the basis of this framework. We make an effort to find the appropriate use for syntactic information, including parent nodes, syntactic paths and term ratios under the machine learning framework. The experiment results show that syntactic paths and term ratios can improve precision of term extraction, including old terms and novel terms. However, the recall rate of novel terms still needs to be increased. This research serves as an example for constructing machine learning based term extraction systems that utilizes linguistic information.

Paper Citation

in Harvard Style

Zhang X., Song Y. and Fang A. (2010). CONDITIONAL RANDOM FIELDS FOR TERM EXTRACTION . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 414-417. DOI: 10.5220/0003077304140417

in Bibtex Style

@conference{kdir10,
author={Xing Zhang and Yan Song and Alex Chengyu Fang},
title={CONDITIONAL RANDOM FIELDS FOR TERM EXTRACTION},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={414-417},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003077304140417},
isbn={978-989-8425-28-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - CONDITIONAL RANDOM FIELDS FOR TERM EXTRACTION
SN - 978-989-8425-28-7
AU - Zhang X.
AU - Song Y.
AU - Fang A.
PY - 2010
SP - 414
EP - 417
DO - 10.5220/0003077304140417