通信学报2018，Vol.39Issue(3)：147-158,12.DOI:10.11959/j.issn.1000-436x.2018044
基于跨平台的在线社交网络用户推荐研究
User recommendation based on cross-platform online social networks
摘要
Abstract
In the field of online social networks on user recommendation, researchers extract users' behaviors as much as possible to model the users. However, users may have different likes and dislikes in different social networks. To tackle this problem, a cross-platform user recommendation model was proposed, users would be modeled all-sided. In this study, the Sina micro blog and the Zhihu were investigated in the proposed model, the experimental results show that the proposed model is competitive. Based on the proposed model and the experimental results, it can be known that modeling users in cross-platform online social networks can describe the user more comprehensively and leads to a better recommendation.关键词
跨平台/用户推荐/在线社交网络/数据挖掘Key words
cross-platform/user recommendation/online social networks/data mining分类
信息技术与安全科学引用本文复制引用
彭舰,王屯屯,陈瑜,刘唐,徐文政..基于跨平台的在线社交网络用户推荐研究[J].通信学报,2018,39(3):147-158,12.基金项目
国家自然科学基金资助项目(No.U1333113, No.61602330) （No.U1333113, No.61602330）
四川省科技支撑计划基金资助项目(No.2014GZ0111) （No.2014GZ0111）
四川省教育厅科研基金资助项目(No.18ZA0404) （No.18ZA0404）
