一种基于LBS的移动个性化推荐系统

随着个性化推荐技术的不断成熟和移动互联网的迅猛发展以及各种移动智能设备在人们的日常生活中扮演着重要的角色。结合LBS和个性化推荐技术,提出一种基于LBS的移动个性化菜品推荐系统。系统通过经纬度对菜品进行地域过滤,从而产生候选推荐集,然后对候选推荐集进行分类或聚类,并且对各类里的候选推荐集采用协同过滤技术进行过滤,从而形成每个类的Top-Ni推荐集,最后将各类的Top-Ni推荐集进行归并并产生最终的推荐集。最后在iPhone平台上实现了系统原型EatStars。

A LBS-based mobile personalized recommendation system

With developing of personalized recommendation technology, the rapid development of mobile Internet and the important role kinds of mobile smart devices played in people's daily life. In this paper, we proposed a LBS-based mobile personalized recommendation system with LBS (Location-based Service) and personalized recommendation technology. At first, the system generated candidate recommendation set by filtering with longitude and latitude; then classified or clustered them and filtered each class by using collaborative filtering algorithm; Finally, we generated the finally result set by merging Top-Ni recommendation set of each class. (We demonstrated an initial prototype of EatStars on the iPhone platform finally)