移动互联网海量用户移动与浏览行为的研究与应用

发布时间：2018-08-23 21:02

【摘要】：随着移动通信技术的发展和智能手机的普及,移动互联网为越来越多的用户提供了便捷的服务,并逐渐成为人们日常生活中不可或缺的一部分。数以亿计的用户每天使用移动智能设备接入移动互联网,并通过其产生了大量的用户数据。在数据价值受到高度认同的今天,如何对海量用户数据加以研究和应用成为了人们关注的焦点。本文由移动互联网海量用户的移动和浏览数据着手,依托分布式处理框架Hadoop,从用户位置信息优化、城市热门区域发现等方面进行了研究,并使用具备普适性的系统框架对用户移动和浏览行为的研究成果进行了可视化呈现。用户位置信息是进行用户移动行为研究的基础,获取用户的精确位置对于用户位置预测、用户重要位置发现等具有重要意义,本文提出了一种基于移动互联网话单数据,对用户位置信息进行精确度优化的方法,并使用真实数据对该方法进行了可行性验证。蕴含海量用户移动和浏览信息的移动互联网数据也为研究城市空间特征提供了机会,本文采用一种具备阈值适应性的方法对我国东北某省六个主要城市进行了热门区域识别,并对各城市热门区域特征的异同点进行了分析。此外,本文重点关注了城市中最重要的区域——永久型热门区域。基于永久型热门区域,我们对城市空间结构特征进行了探究。在对用户移动和浏览行为进行研究的同时,本文也考虑了如何以直观、生动的方式对分析结果进行呈现,我们设计了一套具备普遍适用性的系统框架,并以三个专题的数据库表设计、网页界面实现为例,阐述了该系统的实现。本文基于真实的移动互联网数据,对海量用户的移动和浏览行为进行了分析与挖掘,得到了诸多富有意义的结果。同时,本文还提供了切实可行的大数据可视化实现方案,为研究成果的实际应用提供了便利。
[Abstract]:With the development of mobile communication technology and the popularity of smart phones, mobile Internet has provided more and more users with convenient services, and has gradually become an indispensable part of people's daily life. Hundreds of millions of users use mobile smart devices to access the mobile Internet every day and generate a lot of user data through it. Today, data value is highly recognized, how to study and apply massive user data has become the focus of attention. This paper starts with the mobile and browsing data of massive users of mobile Internet, and researches on the optimization of user location information and the discovery of popular urban areas, relying on the distributed processing framework Hadoop,. A universal system framework is used to visualize the research results of user mobility and browsing behavior. User location information is the basis of user mobile behavior research. It is very important to obtain the exact location of users for user location prediction and important location discovery. In this paper, we propose a new method based on mobile Internet voice sheet data. The accuracy of the user location information is optimized, and the feasibility of the method is verified by using real data. Mobile Internet data containing massive user mobile and browsing information also provide an opportunity to study urban spatial characteristics. In this paper, a threshold adaptive method is used to identify six major cities in Northeast China. The similarities and differences of the characteristics of popular regions in different cities are analyzed. In addition, this paper focuses on the most important area in the city-permanent hot area. Based on the permanent hot area, we explore the characteristics of urban spatial structure. While researching the behavior of user mobile and browsing, this paper also considers how to present the analysis results in an intuitive and vivid way. We have designed a set of system framework with universal applicability. Taking the database table design of three topics and the realization of the web interface as an example, the realization of the system is expounded. Based on the real mobile Internet data, this paper analyzes and excavates the mobile and browsing behaviors of massive users, and obtains many meaningful results. At the same time, this paper also provides a feasible realization scheme of big data visualization, which is convenient for the practical application of the research results.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.5;TP393.0

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