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http://dx.doi.org/10.3745/KTSDE.2013.2.9.603

Estimating Personal and Social Information for Mobile User  

Son, Jeong-Woo (경북대학교 전자전기컴퓨터학부)
Han, Yong-Jin (경북대학교 전자전기컴퓨터학부)
Song, Hyun-Je (경북대학교 전자전기컴퓨터학부)
Park, Seong-Bae (경북대학교 IT대학 컴퓨터학부)
Lee, Sang-Jo (경북대학교 IT대학 컴퓨터학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.2, no.9, 2013 , pp. 603-614 More about this Journal
Abstract
The popularity of mobile devices provides their users with a circumstance that services and information can be accessed wherever and whenever users need. Accordingly, various studies have been proposed personalized methods to improve accessibility of mobile users to information. However, since these personalized methods require users' private information, they gives rise to problems on security. An efficient way to resolve security problems is to estimate user information by using their online and offline behavior. In this paper, for this purpose, it is proposed a novel user information identification system that identifies users' personal and social information by using both his/her behavior on social network services and proximity patterns obtained from GPS data. In the proposed system, personal information of a user like age, gender, and so on is estimated by analyzing SNS texts and POI (Point of Interest) patterns, while social information between a pair of users like family and friend is predicted with proximity patterns between the users. Each identification module is efficiently designed to handle the characteristics of user data like much noise in SNS texts and missing signals in GPS data. In experiments to evaluate the proposed system, our system shows its superiority against ordinary identification methods. This result means that the proposed system can efficiently reflect the characteristics of user data.
Keywords
User Identification; SNS; Proximity; SVM; Gaussian Mixture;
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Times Cited By KSCI : 1  (Citation Analysis)
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