DocumentCode :
3041251
Title :
Consideration about Utilizing Text Architecture for Making Feature Vectors in Classifying Nursing-Care Texts
Author :
Nii, Manabu ; Miyake, S. ; Takahama, Kazunobu ; Uchinuno, Atsuko ; Sakashita, Reiko
Author_Institution :
Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan
fYear :
2013
fDate :
13-16 Oct. 2013
Firstpage :
1817
Lastpage :
1821
Abstract :
Since Japan is one of the most aging countries, it is very important for us to improve the nursing-care quality. For improving the nursing-care quality, a Web-based nursing-care quality improvement system have been proposed and operating experimentally and continuously. A kind of collected data by the Web-based system is freestyle Japanese text called "nursing-care texts". The nursing-care texts are used for evaluating actual nursing-care process. In order 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 phrase based feature vector definition for classifying the nursing-care texts. The dependency relation based feature vector definition has been proposed in our previous work. As another feature vector definition method, we propose a phrase based feature vector definition method. Phrases are found by using the dependency relation analysis and stored into a phrase list. We also define a similarity between phrases because each phrase consists of some kinds of words. From experimental results, we show that our phrase based feature vector contributes the classification performance.
Keywords :
Internet; feature extraction; health care; natural language processing; patient care; text analysis; Web-based nursing-care quality improvement system; computer aided nursing-care text classification system; data collection; dependency relation analysis; freestyle Japanese text; nursing-care experts; nursing-care process evaluation; phrase based feature vector definition; phrase list; phrase similarity; phrase words; text architecture; Conferences; Educational institutions; Feature extraction; Indexes; Medical services; Support vector machine classification; Vectors; Nursing-care; SVM; dependency relations; text classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
Type :
conf
DOI :
10.1109/SMC.2013.313
Filename :
6722066
Link To Document :
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