A development of classification model for smartphone addiction recognition system based on smartphone usage data

Worawat Lawanont, Masahiro Inoue

研究成果: Conference contribution

抄録

The rapid growth of smartphone in recent years has resulted in many syndromes. Most of these syndromes are caused by excessive use of smartphone. In addition, people who tends to use smartphone excessively are also likely to have smartphone addiction. In this paper, we presented the system architecture for e-Health system. Not only we used the architecture for our smartphone addiction recognition system, but we also pointed out important benefits of the system architecture, which also can be adopted by other system. Later on, we presented a development of the classification model for recognizing likelihood of having smartphone addiction. We trained the classification model based on data retrieved from subjects’ smartphone. The result showed that the best model can correctly classify the instance up to 78%.

本文言語English
ホスト出版物のタイトルIntelligent Decision Technologies 2017 - Proceedings of the 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017
編集者Robert J. Howlett, Lakhmi C. Jain, Lakhmi C. Jain, Ireneusz Czarnowski, Robert J. Howlett, Lakhmi C. Jain
出版社Springer Science and Business Media Deutschland GmbH
ページ3-12
ページ数10
ISBN(印刷版)9783319594231
DOI
出版ステータスPublished - 2018
イベント9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017 - Vilamoura, Portugal
継続期間: 2017 6 212017 6 23

出版物シリーズ

名前Smart Innovation, Systems and Technologies
73
ISSN(印刷版)2190-3018
ISSN(電子版)2190-3026

Other

Other9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017
CountryPortugal
CityVilamoura
Period17/6/2117/6/23

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

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