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

页码：354 / +

页数：2

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