计算机应用研究2017，Vol.34Issue(10)：2978-2983,2996,7.DOI:10.3969/j.issn.1001-3695.2017.10.022
一种基于位置社交网络融合多种情景信息的兴趣点推荐模型
UGTM: exploiting various types of contextual information for point-of-interest recommendation on location-based social networks
摘要
Abstract
Since the existing works of POI(point-of-interest) recommendation on location-based social networks(LBSN) focus on mining context information of POI,including the geographical information,comment information and the temporal information,which the comment information of user has not been systematically studied.This paper proposed a unified POI recommendation model,which fused user preference to a POI with temporal information,geographical influence and comment information of user.The model studied the comment information of LBSN by exploiting the latent Dirichlet allocation(LDA) model and modeled the user preference based on the number of user check-in behaviors.Finally,experimental results in real world social network show that the proposed model outperforms state-of-the-art recommendation algorithms in terms of precision and rating error.关键词
协同过滤/兴趣点推荐/位置社交网络/情景建模/主题分析Key words
collaborative filtering/point-of-interest recommendation/location-based social networks/context modeling/topic modeling分类
信息技术与安全科学引用本文复制引用
陈志雄,曾诚,高榕..一种基于位置社交网络融合多种情景信息的兴趣点推荐模型[J].计算机应用研究,2017,34(10):2978-2983,2996,7.基金项目
国家自然科学基金青年基金资助项目(41201404) （41201404）
国家“973”计划资助项目(2012CB719905) （2012CB719905）
