A Genetic Approach for Biomedical Named Entity Recognition

被引：2
作者：
Ekbal, Asif [1 ]
Saha, Sriparna [1 ]
Sikdar, Utpal Kumar [2 ]
Hasanuzzaman, Md [3 ]
机构：
[1] Univ Trento, Trento, Italy
[2] Tata Elxsi, Bangalore, Karnataka, India
[3] West Bengal Ind Dev Crop, Kolkata, W Bengal, India
来源：
22ND INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2010), PROCEEDINGS, VOL 2 | 2010年
关键词：
D O I：
10.1109/ICTAI.2010.125
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we report a classifier ensemble technique using the search capability of genetic algorithm (GA) for Named Entity Recognition (NER) in biomedical domain. We use Maximum Entropy (ME) framework to build a number of classifiers depending upon the various representations of a set of features. The proposed technique is evaluated with the JNLPBA 2004 data sets that yield the overall recall, precision and F-measure values of 67.98%, 71.68% and 69.78%, respectively.
引用
收藏
页码：354 / +
页数：2
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