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

Author:

Hsu Kuo-Wei1ORCID

Affiliation:

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

Abstract

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.

Funder

National Science Council of Taiwan

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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3. Mining Weighted Frequent Patterns from Uncertain Data Streams;Advances in Intelligent Systems and Computing;2019

4. Mining Regular High Utility Sequential Patterns in Static and Dynamic Databases;Advances in Intelligent Systems and Computing;2019

5. A Systematic Evaluation of Mobile Applications for Instant Messaging on iOS Devices;Mobile Information Systems;2017-10-02

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