Event Recommendation in Event-Based Social Networks

被引：0

作者：

Qiao, Zhi ^{[1
,2
,3
]}

Zhang, Peng ^{[1
]}

Zhou, Chuan ^{[1
]}

Cao, Yanan ^{[1
]}

Guo, Li ^{[1
]}

Zhang, Yanchun ^{[4
]}

机构：

[1] Chinese Acad Sci, Inst Informat Engn, Beijing, Peoples R China

[2] Inst Comp Technol, Beijing, Peoples R China

[3] Univ Chinese Acad Sci, Beijing, Peoples R China

[4] Victoria Univ, Melbourne, Vic, Australia

来源：

PROCEEDINGS OF THE TWENTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2014年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the rapid growth of event-based social networks, the demand of event recommendation becomes increasingly important. Different from classic recommendation problems, event recommendation generally faces the problems of heterogenous online and offline social relationships among users and implicit feedback data. In this paper, we present a baysian probability model that can fully unleash the power of heterogenous social relations and efficiently tackle with implicit feedback characteristic for event recommendation. Experimental results on several real-world datasets demonstrate the utility of our method.

引用

页码：3130 / 3131

页数：2

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