@inproceedings{8c81da3750c14fef98da793c73988a3e,
title = "Conditional random fields for term extraction",
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.",
keywords = "Conditional random fields, Syntactic function, Term extraction, Term ratio",
author = "Xing Zhang and Yan Song and Fang, \{Alex Chengyu\}",
year = "2010",
language = "English",
isbn = "9789898425287",
series = "KDIR 2010 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
pages = "414--417",
booktitle = "KDIR 2010 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
note = "International Conference on Knowledge Discovery and Information Retrieval, KDIR 2010 ; Conference date: 25-10-2010 Through 28-10-2010",
}