DocumentCode :
1909024
Title :
Feature Definition Using Dependency Relations between Terms for Improving Nursing-care Text Classification
Author :
Nii, Manabu ; Hirohata, Y. ; Uchinuno, Atsuko ; Sakashita, Reiko
Author_Institution :
Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan
fYear :
2012
fDate :
5-7 Nov. 2012
Firstpage :
110
Lastpage :
115
Abstract :
In order to improve the nursing-care quality, a"Web based Nursing-care Quality Improvement System" have been proposed and operating continuously. In the proposed system, for evaluating actual nursing-care process, freestyle Japanese texts which are called "nursing-care texts" are collected through the Internet in Japan. The nursing-care experts can evaluate actual nursing-care process and recommend some improvements to nurses by reading the collected nursing-care texts carefully. Since the number of nursing-care experts who can evaluate the nursing-care texts is a few, it is hard to do the above mentioned evaluation process for a large number of nurses. To assist nursing-care experts in evaluating the nursing-care texts, a computer aided nursing-care text classification system has been developed. In this paper, we propose a method to improve the classification performance of the computer aided nursing-care text classification system. Dependency relation between terms is extracted from the nursing-care text and used the dependency as a feature value which represents characteristics of the nursing-care text.
Keywords :
Internet; medical computing; patient care; text analysis; Internet; Web based nursing-care quality improvement system; computer aided text classification system; dependency relations; feature definition; freestyle Japanese texts; nursing-care experts; nursing-care process evaluation; Nursing-care; SVM; dependency relation; text classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Trends in Engineering and Technology (ICETET), 2012 Fifth International Conference on
Conference_Location :
Himeji
ISSN :
2157-0477
Print_ISBN :
978-1-4799-0276-7
Type :
conf
DOI :
10.1109/ICETET.2012.68
Filename :
6495268
Link To Document :
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