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스마트폰 어플리케이션 설치 목록을 이용한 사용자 특성 추론
기홍도(Hongdo Ki),이재홍(Jaehong Lee),박희웅(Heewoong Park),채문정(Moon-jung Chae),최상우(Sangwoo Choi),박종헌(Jonghun Park) Korean Institute of Information Scientists and Eng 2018 정보과학회논문지 Vol.45 No.12
Needs for customized services are increasing as a smart phone personalized device, has been used generally. Demographic information is beneficial for customized services, so inferring user traits based various data using statistical learning has been actively studied. This study conducted experiments of inferring user traits with a list of installed applications differed by users’ interest and lifestyle, and may can be accessed easily as a snapshot without explicit permission. Four feature vectors are used for inferring user traits, including vectors using application category or description that can be collected from the application market. Especially, one of the feature vectors is generated by applying Doc2Vec, a text embedding method based on a neural network, to application description. The application selection method we proposed is also used to achieve better performances than could be achieved by using all applications on the list. Last, we collected 100 lists of installed applications for experiments of inferring gender, age, relationship status, residential type, living together or not, income, outcome, height, weight, religion, semester and college, and confirmed effectiveness of proposed feature vectors and the application selection method.