Research And Implementation Of Mobile Terminal Information Recommendation System Based On LBS

With the opening of the 4G network era, the popularity of intelligent terminals, as well as the arrival of the era of mobile Internet, new technologies are being integrated into and changing people’s lives, work, study and other daily activities. In such a trend, all kinds of mobile phone application is booming, services based on the location also in unconsciously penetrate into people’s lives, such as micro channel, microblogging, reading on mobile phone, mobile phone games, people’s life has been facilitated.Under this background, this thesis focuses on location-based services, not only for the research of theoretical, also design and implement an system based on the location of the service. The theoretical part explains the origin of LBS, the development and the industrial environment of LBS at home and abroad, and analyzes the challenges and opportunities faced by the current LBS; Then this thesis gives a detailed analysis of LBS and related fields:LBS part introduces its concept, composition, application, positioning technology; Related fields introduced mobile Internet, maps and some algorithms (such as geohash etc.). System design and implementation section, designed and implemented an application of LBS based on client of Android platform, back-end services of J2EE platform, log analysis system of Hadoop, the thesis describes the process of system’s design and development in detail, as well as the the final effect of system. In order to make the theory and technology involved in the system more uncertain, the thesis also introduces some relevant theory and technical field of recommendation system. The basic concept, classification, and cold start problems of the system are introduced in this thesis. The related technical description includes Android system, J2EE framework and some transmission protocols and data formats.In this thesis, a new location based recommendation method is proposed, which combines the user behavior data analysis with the large data platform to predict the user’s preferences. Although there is no mature location based recommendation method, but the wealth left behind by predecessors, combined with our efforts, Research in this field will be more in-depth, and the road will be more extensive.