An adaptive social influence propagation model based on local network topology

被引：0

作者：

Liu, Haifeng ^{[1
]}

Hu, Zheng ^{[1
]}

Tian, Hui ^{[1
]}

Zhou, Dian ^{[1
]}

机构：

[1] Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Ministry of Education

来源：

Lecture Notes in Business Information Processing | 2013年 / 152卷

关键词：

Local network topology; Propagation model; Social influence; Social recommendation;

D O I：

10.1007/978-3-642-39878-0_2

中图分类号：

学科分类号：

摘要：

With the wide application of all kinds of social network services, social recommendation has attracted many attentions from academia and industry. Different from traditional recommender systems, social influence plays a significant role in social recommendation. However, many existing approaches cannot effectively simulate the influence propagation and the computation of social influence is complex. This leads to the low prediction accuracy. Hence, this paper proposes an adaptive social influence propagation model to address this problem. Moreover, we present a simple and fast social influence computation method according to the local network topology, which can provide distinguishing influences for one user depending on its neighbors. To demonstrate the performance, we design the shortest path with maximum propagation strategy and experiments are conducted to compare our model with other social influence propagation approaches on the real data set. Empirical results show that both the quality of prediction and coverage have remarkable improvement, especially with few ratings. Springer-Verlag Berlin Heidelberg 2013.

引用

页码：14 / 26

页数：12

共 22 条

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