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ADHD/Autism Disorders Clustering Method Using Korean Morphology Analyzer with Observed Behaviors Data

Title
ADHD/Autism Disorders Clustering Method Using Korean Morphology Analyzer with Observed Behaviors Data
Authors
Kang, Won SeokYun, Sang HunKwon, Hyeong OhChoi, Moon JongKang, Jung Bae
DGIST Authors
Kang, Won Seok; Yun, Sang Hun; Kwon, Hyeong Oh; Choi, Moon Jong; Kang, Jung Bae
Issue Date
2014
Citation
Global Journal on Technology, 5, 49-52
Type
Article
ISSN
2147-5369
Abstract
In this paper, we propose a method to cluster Attention Deficit/Hyperactivity Disorder (ADHD) and autism disorder using observed behaviors data. We utilized a Korean morphology analyzer to analysis features of the observed behaviors data which was recorded by text type. The proposed method aims to support an assistance tool to a special education and rehabilitation teachers to reduce the educating efforts. To show the efficiency of the proposed method, we used the historical text-typed records accumulated in the Research Institute of Special Education and Rehabilitation Science (RISPERS), Daegu University. The data had been recorded for 5 years. As a result of simulation, we confirmed that the proposed method achieved the clustering accuracy of 60% by choosing and evaluating the random result sample of 200 children of disorders.
URI
http://hdl.handle.net/20.500.11750/13371
http://archives.sproc.org/index.php/P-ITCS/article/view/3044/2454
Publisher
Academic World Education & Research Center
Related Researcher
  • Author Kang, Won-Seok  
  • Research Interests Data Mining & Machine Learning for Text & Multimedia, Brain-Sense-ICTConvergence Computing, Computational Olfaction Measurement, Simulation&Modeling
Files:
There are no files associated with this item.
Collection:
ETC1. Journal Articles
Division of Electronics & Information System1. Journal Articles


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