Demographic information prediction: a portrait of smartphone application Users

Qin, Zhen, Wang, Yilei, Cheng, Hongrong, Zhou, Yingjie, Sheng, Zhengguo and Leung, Victor C M (2016) Demographic information prediction: a portrait of smartphone application Users. IEEE Transactions on Emerging Topics in Computing (99). ISSN 2168-6750

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Abstract

Demographic information is usually treated as private data (e.g., gender and age), but has been shown great values in personalized services, advertisement, behavior study and other aspects. In this paper, we propose a novel approach to make efficient demographic prediction based on smartphone application usage. Specifically, we firstly consider to characterize the data set by building a matrix to correlate users with types of categories from the log file of smartphone applications. Then, by considering the category-unbalance problem, we make use of the correlation between users’ demographic information and their requested Internet resources to make the prediction, and propose an optimal method to further smooth the obtained results with category neighbors and user neighbors. The evaluation is supplemented by the dataset from real world workload. The results show advantages of the proposed prediction approach compared with baseline prediction. In particular, the proposed approach can achieve 81.21% of Accuracy in gender prediction. While in dealing with a more challenging multi-class problem, the proposed approach can still achieve good performance (e.g., 73.84% of Accuracy in the prediction of age group and 66.42% of Accuracy in the prediction of phone level).

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA0329 Engineering mathematics. Engineering analysis
Depositing User: Zhengguo Sheng
Date Deposited: 13 May 2016 09:33
Last Modified: 08 Mar 2017 09:40
URI: http://sro.sussex.ac.uk/id/eprint/60886

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