基于谱聚类的手机用户日移动行为分析
Cell Phone User Daily Mobility Pattern Analysis Based on Spectrum Clustering Method
DOI: 10.12677/HJDM.2012.24008, PDF, HTML,  被引量 下载: 3,818  浏览: 13,915  国家科技经费支持
作者: 黄 涛：武汉虹信通信技术有限责任公司；周 晨, 黄本雄, 涂 来*：华中科技大学电子与信息工程系
关键词: 移动行为模式；谱聚类；用户通话清单；Mobility Pattern; Spectrum Clustering; Call Detail Records
摘要: 随着通信业的发展和手机的普及，手机记录了大量的人类社交行为数据，其中包括了每个用户每次通话行为以及当时通话的地理位置。如何通过这些数据揭示出人类移动行为的内在规律，从而找到用户的移动特性做出相应的移动行为预测，成为了一个重要的课题。本文通过谱聚类方法，分析手机通话数据，通过提取特征，建立日行为路径相似度的模型，对一个典型用户的日移动行为进行同质归并处理，从而找出以天为单位相同的移动路径。并从星期和活动地域的角度，针对聚类结果中不同簇的日移动路径分别进行了统计分析。
Abstract: Along with the development of telecommunication industry and the popularization of mobile phones, cell phones make records of human social behavior data including the call volume, calling patterns, and the location of the cellular phones of their subscribers. How to reveals the rules of human movement behavior based on those data, to make the mobility behavior prediction, has become a rising issue. This article extract characteristics of user mobility and find several kinds of their daily paths though call detail records using spectrum clustering method. The regularity of the same kind of the daily path with different time and special information has been analyzed based on statistic method.
文章引用：黄涛, 周晨, 黄本雄, 涂来. 基于谱聚类的手机用户日移动行为分析[J]. 数据挖掘, 2012, 2(4): 38-42. http://dx.doi.org/10.12677/HJDM.2012.24008

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