Exploring Social Influence on Location-Based Social Networks

Yu Ting Wen, Po Ruey Lei, Wen Chih Peng, Xiao Fang Zhou

研究成果: Conference contribution同行評審

35 引文 斯高帕斯(Scopus)

摘要

Recently, with the advent of location-based social networking services (LBSNs), travel planning and location-aware information recommendation based on LBSNs have attracted much research attention. In this paper, we study the impact of social relations hidden in LBSNs, i.e., The social influence of friends. We propose a new social influence-based user recommender framework (SIR) to discover the potential value from reliable users (i.e., Close friends and travel experts). Explicitly, our SIR framework is able to infer influential users from an LBSN. We claim to capture the interactions among virtual communities, physical mobility activities and time effects to infer the social influence between user pairs. Furthermore, we intend to model the propagation of influence using diffusion-based mechanism. Moreover, we have designed a dynamic fusion framework to integrate the features mined into a united follow probability score. Finally, our SIR framework provides personalized top-k user recommendations for individuals. To evaluate the recommendation results, we have conducted extensive experiments on real datasets (i.e., The Go Walla dataset). The experimental results show that the performance of our SIR framework is better than the state-of the-art user recommendation mechanisms in terms of accuracy and reliability.

原文English
主出版物標題Proceedings - 14th IEEE International Conference on Data Mining, ICDM 2014
編輯Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1043-1048
頁數6
2015-January
版本January
ISBN(電子)9781479943029
DOIs
出版狀態Published - 26 1月 2015
事件14th IEEE International Conference on Data Mining, ICDM 2014 - Shenzhen, 中國
持續時間: 14 12月 201417 12月 2014

出版系列

名字Proceedings - IEEE International Conference on Data Mining, ICDM
號碼January
2015-January
ISSN(列印)1550-4786

Conference

Conference14th IEEE International Conference on Data Mining, ICDM 2014
國家/地區中國
城市Shenzhen
期間14/12/1417/12/14

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