基于LBSN的商业选址推荐系统的研究与实现

随着智能移动设备的发展和普及,空间定位技术不断成熟,基于位置的社交网络(Location-based Social Network,LBSN)得到了广泛应用。大量用户在LBSN签到,以及针对签到进行的评论不仅记录了用户的时空行为轨迹,也为研究用户行为模式和特征偏好提供了巨大的机会。提出一种基于LBSN签到数据的商业店铺选址推荐系统,首先分析用户在LBSN上的签到时间、签到地点、签到商铺类型3个方面的特征；然后提出4个影响商铺选址的因素:多样性、竞争性、相关性和客流性；最后实现商业选址推荐系统,并根据选址因素生成最优候选。并以此为基础进行相关实验来验证推荐结果,结果符合相关预期。

Research and Implementation of Commercial Site Recommendation System Based on LBSN

With the development and popularization of smart mobile devices,spatial positioning technology continues to develop,and based on this,location-based social network is widely used.The majority of users check in LBSN,and comment on check-in activity,which not only record the spatial-temporal behavior track,but also provide great opportunities for us to study user behavior patterns and characteristics of preference.This paper proposed a commercial site re-commendation system based on LBSN.Firstly,it analysed the characteristics about the check-in time,the check-in location and the category of check-in retail in LBSN.Then it proposed four kinds of factors that affect retail location:diversity,competitive,relevance,passenger flow.Finally the system was implemented that can provide the best candidate based on various factors.The paper used those as the basis for experiments to verify the recommendation result.The results comply with the relevant expectations.