LBSN下基于用户朋友关系的商业POI推荐  

Commercial POI recommendation based on user’s friend relationship in LBSN

作　　者：仲秋雁[1] 王涵雪 ZHONG Qiuyan;WANG Hanxue(School of Economics and Management,Dalian University of Technology,Dalian 116024,China)

机构地区：[1]大连理工大学经济管理学院,大连116024

出　　处：《系统工程理论与实践》2021年第10期2501-2511,共11页Systems Engineering-Theory & Practice

基　　金：国家自然科学基金重点项目(71533001)。

摘　　要：基于位置的社交网络(location-based social network,LBSN)随着定位技术与智能终端技术的发展拥有了极大研究价值,其中商业兴趣点(point-of-interest,POI)推荐成为一大研究视角,且随着数据量成倍增长,成为了必须解决的问题.但当前推荐更多关注于考虑地理因素的推荐,对社交关系的考虑较少,为了改进推荐效果,本文重点考虑社交关系中朋友关系的使用,提出了基于带权水波模型的商业POI推荐方法.该方法基于用户朋友关系和交互信息构建偏好网络,在网络中模拟水波扩散,考虑波纹重叠处的偏好增强情况,计算候选POI在目标用户网络中的偏好传播,并通过关系权重来体现地理因素和时间因素对偏好传播的影响,保证相似度计算的准确,以此形成用户推荐列表.并通过Yelp的数据实验证明该算法能取得较优推荐效果.Location-based social network(LBSN) has great research value with the development of location technology and smart terminal technology.At the same time commercial point-of-interest(POI)recommendation has become a research perspective,and with the increase of data volume,it has become a problem that must be solved.However,the current recommendation is more concerned with the recommendation of geographical factors,and the consideration of social relationships is relatively small.In order to improve the effect of recommendation,this paper focuses on the use of friend relationships in social relationships,and proposes a commercial point-of-interest(POI) recommendation method based on the weighted ripple net model.The method builds a preference network based on friends ’ relationship and interaction information,and simulates water wave diffusion in the network to consider preference enhancements at ripple overlap.With the simulating,it calculates the preference propagation of candidate point-of-interest(POI) in the target user network,and reflects the effect of geographic factors and time factors on preference propagation through the weight of the relationship to ensure the accuracy of the similarity calculation.Thus forming a recommended list of users.Finally,the data experiments on Yelp show that the algorithm can achieve better recommendation results.

关 键 词：兴趣点推荐 基于位置的社交网络 带权水波模型 偏好网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]