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活动社交网络EBSNs上冷启动推荐方法
引用本文:仲兆满,李恒,管燕,李慧.活动社交网络EBSNs上冷启动推荐方法[J].重庆邮电大学学报(自然科学版),2021,33(5):834-843.
作者姓名:仲兆满  李恒  管燕  李慧
作者单位:江苏海洋大学 计算机工程学院,江苏 连云港222005;江苏省海洋资源开发研究院,江苏 连云港222005;江苏海洋大学 计算机工程学院,江苏 连云港222005
基金项目:国家自然科学基金(61403156);江苏省高校自然科学研究项目(9KJB520004);连云港高新区科技项目(ZD201912)
摘    要:活动社交网络(event-based social networks,EBSNs)为用户提供了方便的组织、参加和分享社交活动的平台,由于冷启动用户/活动缺少丰富的历史数据,EBSNs上冷启动用户/活动的推荐是难点问题.面向EBSNs给出了包含活动、主办方和用户的表示模型,提出了向冷启动用户推荐活动,以及将冷启动活动推荐给用户的模型和基于随机游走的节点重要度计算方法.在分析用户参加活动行为模式的基础上,使用真实的EBSNs平台-豆瓣同城验证所提方法的有效性.提出的向冷启动用户推荐活动方案与群组活动推荐相比,评价指标有了明显的提升.该研究构建的向冷启动用户推荐活动,以及将冷启动活动推荐给用户的模型能有效解决活动社交网络上冷启动用户/活动的推荐问题.

关 键 词:活动社交网络  表示模型  冷启动推荐  用户行为模式
收稿时间:2021/5/30 0:00:00
修稿时间:2021/7/5 0:00:00

Cold-start recommendation method in event-based social networks
ZHONG Zhaoman,LI Heng,GUAN Yan,LI Hui.Cold-start recommendation method in event-based social networks[J].Journal of Chongqing University of Posts and Telecommunications,2021,33(5):834-843.
Authors:ZHONG Zhaoman  LI Heng  GUAN Yan  LI Hui
Institution:School of ComputerEngineering, Jiangsu Ocean University, Lianyungang 222005, P. R. China;Jiangsu Academy of Marine Resources Development, Lianyungang 222005, P. R. China
Abstract:Event-based social networks (EBSNs) provide convenient platforms of organizing, participating and sharing social events to users. This paper studies the recommendation of cold-start users/events in EBSNs. Due to the lack of rich historical data of cold-start users/events, the recommendation of cold-start users/events in EBSNS is a difficult problem. This work proposed EBSNs representation model containing event, sponsor and user. Furthermore, the models were proposed for recommending events to cold-start users or users with cold-start events, and the method of calculating node importance based on random walk was proposed. The effectiveness of this method was verified with the real EBSN platform, Douban Event. Compared with group event recommendation, the evaluation index of the proposed event recommendation scheme for cold-start users has been significantly improved. The model constructed to recommend events to cold-start users and to recommend cold-start events to users can effectively solve the recommendation problem of cold-start users/events in EBSNs.
Keywords:event-based social network  representation model  cold-start recommendation  user behavior pattern
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