基于粗糙集和LBS的Android系统研究与应用

发布时间：2018-10-21 17:31

【摘要】：目前手机应用种类繁多,参差不齐,其中一个重要组成部分就是基于位置服务(LBS)的应用。随着WiFi的覆盖范围越来越大、定位技术的日趋成熟和手机的传输速率越来越快更加的促进了 LBS的迅猛发展。当前LBS的发展方向正趋向于个性化,如何满足用户个性化需求,成为基于LBS应用的一个难点。本文先从整体上介绍了国内外手机操作系统的现状、位置服务的现状和个性化推荐方面的现状,然后介绍Android的体系结构,分析了 Android应用程序的组成,然后对几种常用的定位技术进行了介绍,接着对本系统要用到的百度地图进行介绍,接着介绍了几种个性化推荐算法,并对粗糙集理论进行研究,最后把粗糙集理论应用到个性化推荐中来。通过对本文采用的基于粗糙集理论和LBS的推荐模型进行实验,通过对实验数据的分析,表明本文推荐算法能够取得很好的推荐效果。本文算法综合了用户信息,包括其个人基本信息和兴趣信息及用户的位置信息,能更准确地计算用户的相似度,从而提高了推荐的质量。本系统经测试运行流畅稳定,可以作为一款基于LBS的地图个性化服务软件。本文在这些基础上开发了一款基于Android的地图个性化服务软件,该软件界面简洁,功能全面,运行流畅,主要的功能包括市内线路查询,周边搜索,定位,个性化推荐,个性化商品在线购买,视图切换,实时自我定位,路线规划,天气预报和打车等功能。
[Abstract]:At present, there are many kinds of mobile phone applications, one of the important components is the application based on location service (LBS). With the increasing coverage of WiFi, the increasingly mature positioning technology and the faster and faster transmission rate of mobile phones, the rapid development of LBS has been promoted. At present, the development direction of LBS is moving towards individuation. How to meet the individual needs of users has become a difficult point in LBS based applications. This paper first introduces the current situation of mobile phone operating system at home and abroad, the status quo of location service and personalized recommendation, then introduces the architecture of Android, and analyzes the composition of Android application program. Then several common positioning techniques are introduced, then the Baidu map used in this system is introduced, several personalized recommendation algorithms are introduced, and the rough set theory is studied. Finally, rough set theory is applied to personalized recommendation. Through the experiment of the recommendation model based on rough set theory and LBS, and through the analysis of the experimental data, it is shown that the recommendation algorithm in this paper can achieve a good recommendation effect. This algorithm integrates user information, including its basic information, interest information and user location information, which can calculate user similarity more accurately and improve the quality of recommendation. The system runs smoothly and stably, and can be used as a map personalization service software based on LBS. In this paper, a map personalization service software based on Android is developed. The software has simple interface, comprehensive function and smooth running. The main functions include city line inquiry, peripheral search, location, personalized recommendation, etc. Personalized goods online purchase, view switching, real-time self-positioning, route planning, weather forecast and taxi functions.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP18;TP316

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