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User Profile System Based on Sentiment Analysis for Mobile Edge Computing

Sang-Min Park1, Young-Gab Kim2, *

1 Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea.
2 Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul, 05006, Korea.

* Corresponding Author: Young-Gab Kim. Email: email.

Computers, Materials & Continua 2020, 62(2), 569-590.


Emotions of users do not converge in a single application but are scattered across diverse applications. Mobile devices are the closest media for handling user data and these devices have the advantage of integrating private user information and emotions spread over different applications. In this paper, we first analyze user profile on a mobile device by describing the problem of the user sentiment profile system in terms of data granularity, media diversity, and server-side solution. Fine-grained data requires additional data and structural analysis in mobile devices. Media diversity requires standard parameters to integrate user data from various applications. A server-side solution presents a potential risk when handling individual privacy information. Therefore, in order to overcome these problems, we propose a general-purposed user profile system based on sentiment analysis that extracts individual emotional preferences by comparing the difference between public and individual data based on particular features. The proposed system is built based on a sentiment hierarchy, which is created by using unstructured data on mobile devices. It can compensate for the concentration of single media, and analyze individual private data without the invasion of privacy on mobile devices.


Cite This Article

APA Style
Park, S., Kim, Y. (2020). User profile system based on sentiment analysis for mobile edge computing. Computers, Materials & Continua, 62(2), 569-590.
Vancouver Style
Park S, Kim Y. User profile system based on sentiment analysis for mobile edge computing. Comput Mater Contin. 2020;62(2):569-590
IEEE Style
S. Park and Y. Kim, "User Profile System Based on Sentiment Analysis for Mobile Edge Computing," Comput. Mater. Contin., vol. 62, no. 2, pp. 569-590. 2020.


cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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