A Dictionary-Based Approach for Identifying Biomedical Concepts-Reference-Cited by-同舟云学术

A Dictionary-Based Approach for Identifying Biomedical Concepts

Published:2017-02 Issue:09 Volume:31 Page:1757004
ISSN:0218-0014
Container-title:International Journal of Pattern Recognition and Artificial Intelligence
language:en
Short-container-title:Int. J. Patt. Recogn. Artif. Intell.

Author:

Gong Lejun¹,Yang Ronggen²,Liu Quan¹,Dong Zhenjiang³,Chen Hong³,Yang Geng¹

Affiliation:

1. Jiangsu Key Lab of Big Data Security and Intelligent Processing, Jiangsu High Technology Research Key Lab for Wireless Sensor Networks, College of Computer Science & Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210003, P. R. China

2. College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing, 211169, P. R. China

3. Zhongxing Telecommunication Equipment Corporation, Shenzhen, 518057, P. R. China

Abstract

In this research, we provided a dictionary-based approach for identifying biomedical concepts from the literature. The approach first crawled experimental corpus by E-utilities and built a concept dictionary. Then, we developed an algorithm called Variable-step Window Identification Algorithm (VWIA) for matching biomedical concepts based on preprocessing, POS tagging and the formation of phrase block. The approach could identify embedded biomedical concepts and new concepts, which could identify concepts more completely. The proposed approach obtain 95.0% F-measure overall for the test dataset. Thus, it is promising for the method of biomedical text mining.

Funder

National Natural Science Foundation of China

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S021800141757004X

Reference29 articles.

1. Named Entity Recognition for Bacterial Type IV Secretion Systems

2. Information technology to the rescue!

3. A survey of current work in biomedical text mining

4. AUTMINER: A SYSTEM FOR EXTRACTING ASD-RELATED GENES USING TEXT MINING

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