国防科技大学学报2017，Vol.39Issue(1)：74-80,7.DOI:10.11887/j.cn.201701012
用户日常频繁行为模式挖掘
Mining user frequent behavior patterns in daily life
摘要
Abstract
Research focused on how to mine frequent daily behavior patterns of users on smartphones feasibly and efficiently was started.Firstly, a frequent behavior patterns mining framework based on smartphones was proposed.Secondly, a dynamic sliding window algorithm DSW(dynamic slide window) to decrease the context baskets in quantity and improve mining efficiency was proposed.Furthermore, a frequent patterns mining algorithm WePM(weighted pattern mining) which takes both frequency and duration of context occurrence into consideration was developed.On the basis of the above preparation, the mining framework and algorithm were verified experimentally with the context data from 21 users over 6 weeks.Results indicate that the proposed framework and frequent patterns mining algorithm can feasibly and efficiently run on resources limited smartphones to mine daily behavior patterns, and then to reflect users' lifestyles.Finally, the patterns from two perspectives, namely behavior patterns in different locations and time periods are visualized, which benefits the users to realize their daily behavior patterns at any time.关键词
移动数据挖掘/移动感知/行为模式Key words
mobile data mining/mobile sensing/behavior patterns分类
信息技术与安全科学引用本文复制引用
史殿习,李寒,杨若松,莫晓赟,魏菁..用户日常频繁行为模式挖掘[J].国防科技大学学报,2017,39(1):74-80,7.基金项目
国家自然科学基金资助项目(61202117,91118008) （61202117,91118008）
