Location Recommendations Based on Multi-view Learning and Attention-Enhanced Graph Networks

Junxin Chen, Kuijie Lin, Xiang Chen*, Xijun Wang, Terng Yin Hsu

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Personalized location recommendation plays a very important role in location-based social networks, from which both users and service providers can benefit from. In spite of the significant endeavors that have been made towards acquiring knowledge on location attributes and user inclinations, it is still faced with serious data sparsity problems. In this paper, we propose a personalized location recommendation model based on graph neural networks with multi-view learning to obtain effective representations of mobile users and locations from different heterogeneous graphs. We also design an attention-enhanced mechanism to explore the implicit interactions between mobile users and locations themselves. Conducting adequate comparative experiments on two real-world telecom datasets has demonstrated that our model achieves superior performance. Additionally, our model has been proven effective in addressing data sparsity issues.

原文English
主出版物標題Big Data and Social Computing - 8th China National Conference, BDSC 2023, Proceedings
編輯Xiaofeng Meng, Yang Chen, Liming Suo, Qi Xuan, Zi-Ke Zhang
發行者Springer Science and Business Media Deutschland GmbH
頁面83-95
頁數13
ISBN(列印)9789819939244
DOIs
出版狀態Published - 2023
事件8th China National Conference on Big Data and Social Computing, BDSC 2023 - Urumqi, China
持續時間: 15 7月 202317 7月 2023

出版系列

名字Communications in Computer and Information Science
1846 CCIS
ISSN(列印)1865-0929
ISSN(電子)1865-0937

Conference

Conference8th China National Conference on Big Data and Social Computing, BDSC 2023
國家/地區China
城市Urumqi
期間15/07/2317/07/23

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