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%.

元の言語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
出版者Springer Science and Business Media Deutschland GmbH
ページ3-12
ページ数10
73
ISBN(印刷物)9783319594231
DOI
出版物ステータス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(印刷物)2190-3018
ISSN(電子版)2190-3026

Other

Other9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017
Portugal
Vilamoura
期間17/6/2117/6/23

Fingerprint

Smartphones
Addiction
Health
System architecture

ASJC Scopus subject areas

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

これを引用

Lawanont, W., & Inoue, M. (2018). A development of classification model for smartphone addiction recognition system based on smartphone usage data. : Intelligent Decision Technologies 2017 - Proceedings of the 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017 (巻 73, pp. 3-12). (Smart Innovation, Systems and Technologies; 巻数 73). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-59424-8_1

A development of classification model for smartphone addiction recognition system based on smartphone usage data. / Lawanont, Worawat; Inoue, Masahiro.

Intelligent Decision Technologies 2017 - Proceedings of the 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017. 巻 73 Springer Science and Business Media Deutschland GmbH, 2018. p. 3-12 (Smart Innovation, Systems and Technologies; 巻 73).

研究成果: Conference contribution

Lawanont, W & Inoue, M 2018, A development of classification model for smartphone addiction recognition system based on smartphone usage data. : Intelligent Decision Technologies 2017 - Proceedings of the 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017. 巻. 73, Smart Innovation, Systems and Technologies, 巻. 73, Springer Science and Business Media Deutschland GmbH, pp. 3-12, 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017, Vilamoura, Portugal, 17/6/21. https://doi.org/10.1007/978-3-319-59424-8_1
Lawanont W, Inoue M. A development of classification model for smartphone addiction recognition system based on smartphone usage data. : Intelligent Decision Technologies 2017 - Proceedings of the 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017. 巻 73. Springer Science and Business Media Deutschland GmbH. 2018. p. 3-12. (Smart Innovation, Systems and Technologies). https://doi.org/10.1007/978-3-319-59424-8_1
Lawanont, Worawat ; Inoue, Masahiro. / A development of classification model for smartphone addiction recognition system based on smartphone usage data. Intelligent Decision Technologies 2017 - Proceedings of the 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017. 巻 73 Springer Science and Business Media Deutschland GmbH, 2018. pp. 3-12 (Smart Innovation, Systems and Technologies).
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