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Mobile Information Systems
Volume 2017, Article ID 3689309, 18 pages
Research Article

Efficiently and Effectively Mining Time-Constrained Sequential Patterns of Smartphone Application Usage

Department of Computer Science, National Chengchi University, No. 64, Sec. 2, Zhi Nan Rd., Wen Shan District, Taipei 11605, Taiwan

Correspondence should be addressed to Kuo-Wei Hsu; wt.ude.uccn@ushwk

Received 9 August 2016; Revised 14 November 2016; Accepted 1 December 2016; Published 16 January 2017

Academic Editor: Sergio Mascetti

Copyright © 2017 Kuo-Wei Hsu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Today, we have the freedom to install and use all kinds of applications on smartphones, thanks to the development of mobile communication and computing technologies. Undoubtedly, the system and application developers are eager to know how we use the applications on our smartphones in our daily life and so are the researchers. In this paper, we present our work on developing a pattern mining algorithm and applying it to smartphone application usage log collected from tens of smartphone users for several years. Our goal is to mine the sequential patterns each of which presents a series of application uses and satisfies a constraint on the maximum time interval between two application uses. However, we cannot mine such patterns by general algorithms and will miss some patterns by using the widely used implementation of the advanced algorithm specifically designed for time-constrained sequential pattern mining. We not only present an algorithm that can efficiently and effectively mine the patterns in which we are interested but also discuss and visualize the mined patterns. Our work could potentially support the related studies.