@Article{cmc.2020.08666,
AUTHOR = {Sang-Min Park, Young-Gab Kim},
TITLE = {User Profile System Based on Sentiment Analysis for Mobile Edge Computing},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {62},
YEAR = {2020},
NUMBER = {2},
PAGES = {569--590},
URL = {http://www.techscience.com/cmc/v62n2/38265},
ISSN = {1546-2226},
ABSTRACT = {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.},
DOI = {10.32604/cmc.2020.08666}
}