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    题名: Effectively mining time-constrained sequential patterns of smartphone application usage
    作者: Hsu, Kuo-Wei
    徐國偉
    贡献者: 資訊科學系
    关键词: Data mining;Information management;Signal encoding;Smartphones;Application developers;Log mining;Mobile Technology;Sequential pattern mining algorithm;Sequential patterns;Smart-phone applications;Technical details;Usage patterns;Filtration
    日期: 2017-01
    上传时间: 2017-08-03 14:12:58 (UTC+8)
    摘要: With the rapid development of mobile technology, today users have the freedom to download, install, and use various applications on smartphones. For system and application developers, it is certainly advantageous to better understand how users use the applications on their smartphones. To achieve this, we perform pattern mining on real-world data collected from tens of smartphone users for several years. We aim to mine the sequential patterns each of which satisfies a constraint on the maximum time interval between two adjacent application uses. However, we cannot mine all such patterns by first using the time constraint to filter the data and then using a general sequential pattern mining algorithm, neither can we do so by using the stateof-the-art implementation of the algorithm dedicated to mine sequential patterns satisfying the time constraint. In this paper, we present a solution to the problem of mining time-constrained sequential patterns with technical details, and we present the results that will be beneficial to the related studies. © 2017 ACM.
    關聯: Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017,
    11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017; Beppu; Japan; 5 January 2017 到 7 January 2017; 代碼 126221
    数据类型: conference
    DOI 連結: http://dx.doi.org/10.1145/3022227.3022265
    DOI: 10.1145/3022227.3022265
    显示于类别:[資訊科學系] 會議論文

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