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Author Nii, M. ♦ Takahama, K. ♦ Uchinuno, A. ♦ Sakashita, R.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Medical services ♦ Support vector machines ♦ Training data ♦ Feature extraction ♦ Decision trees ♦ Sociology ♦ Statistics
Abstract In this paper, we propose a method of nursing-care text classification. We have proposed some nursing-care classification methods using fuzzy systems, standard three-layer neural networks, and support vector machines. Also we have proposed several types of feature vector definitions for expressing free style Japanese texts into numerical vectors. This paper proposes a novel feature vector definition and a support vector machine utilizing a decision tree (SVM-BDT) based classification system. From experimental results, the effectiveness of both feature definition and SVM-BDT-based classification system is shown.
Description Author affiliation: Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan (Nii, M.; Takahama, K.) || Coll. of Nursing Art & Sci., Univ. of Hyogo, Akashi, Japan (Uchinuno, A.; Sakashita, R.)
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-08-02
Publisher Place Turkey
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781467374286
Size (in Bytes) 168.97 kB
Page Count 5
Starting Page 1
Ending Page 5


Source: IEEE Xplore Digital Library