Exploring influence among participants for event recommendation

机译：探索参与者对活动推荐的影响

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摘要

Event-based Social Networks (EBSN) are popular for organizing offline social events nowadays. In this paper, we develop a new model for event recommendation on EBSNs, which exploits the influence of existing participants, who have expressed willingness to join, on new participants in addition to other context information. Utilizing the participant influence can improve the effectiveness of event recommendation. Experiments on real datasets confirm that the consideration of participant influence can lead to more accurate prediction, offering better event recommendation.

机译：基于事件的社交网络（EBSN）如今在组织离线社交活动中很受欢迎。在本文中，我们开发了一种针对EBSN的事件推荐的新模型，该模型利用了表达了加入意愿的现有参与者对其他参与者以及其他上下文信息的影响。利用参与者的影响可以提高事件推荐的有效性。对真实数据集的实验证实，考虑参与者的影响可以导致更准确的预测，并提供更好的事件推荐。

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来源
《Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining》|2016年|417-420|共4页
会议地点 San Francisco(US)
作者
Yi Liao; Xinshi Lin; Wai Lam;
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作者单位

Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong;

Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong;

Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Social network services; Context; Registers; Mathematical model; Context modeling; History;

机译：社交网络服务;上下文;寄存器;数学模型;上下文建模;历史;

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Exploring influence among participants for event recommendation

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