多因素融合的个性化位置推荐算法  

Personalized Location Recommendation Algorithm Mixing Multi-factors

作　　者：代仕芳[1] 李燕[1] 海凛[2] DAI Shifang 1,LI Yan 1,HAI Lin 2(1.College of Information and Engineering,Nanjing University of Finance and Economics,Nanjing 210046,China;2.College of Electronic and Optical Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210023,Chin)

机构地区：[1]南京财经大学信息工程学院,南京210046 [2]南京邮电大学电子与光学工程学院,南京210023

出　　处：《计算机工程》2018年第6期300-304,310,共6页Computer Engineering

基　　金：江苏省自然科学基金(BK20161023);江苏省高校自然科学基金(16KJB520015);南京财经大学校级预研究项目(YYJ201417)

摘　　要：位置推荐中影响推荐结果的主要因素有地理位置、个人爱好、社会关系以及时间周期,为有效融合4个影响因素并进行个性化位置推荐,针对每个因素构建对应的选择概率模型,并分析各因素对用户选择的影响力,在此基础上,提出一种启发式推荐算法。实验结果表明,与传统的基于位置的推荐算法相比,该算法性能更好,推荐的结果更能被用户所接受。The main factors that influence the recommendation results in location recommendation system include location,personal interest,social relationship and time cycle.In order to effectively integrate 4 factors to personalized location recommendation,the corresponding selection probability model is constructed for each factor.The influence of 4 factors on user selection is analyzed.Finally,the heuristic recommendation algorithm is proposed by combining 4 factors.Experimental results show that,compared with the traditional location-based recommendation algorithm,the proposed algorithm has better performance and the recommended results are more acceptable to users.

关 键 词：基于位置的社会网络 推荐算法 社会关系 签到集 多因素 

分 类 号：TP309.2[自动化与计算机技术—计算机系统结构]