An efficient location recommendation scheme based on clustering and data fusion. (July 2019)

• Record Type: Journal Article
• Authors: Cai, Wenjie; Wang, Yufeng; Lv, Ruheng; Jin, Qun
• Is Part Of: Computers & electrical engineering. Volume 77(2019)
• Page Start: 289
• Page End: 299
• Publication Date: 2019-07
• Subjects: Location recommendation -- Data fusion -- Community detection -- Collaborative filtering; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.06.006
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Recently, location-based social networks (LBSNs) have witnessed a significant development, and have attracted millions of mobile users to share their locations and location-related contents. Due to the huge data in LBSNs, it is imperative to design an efficient location recommendation scheme for abundant users. But most of existing works suffer from poor accuracy and efficiency. On one hand, the traditional user-based collaborative filtering (CF) methods only focus on user characteristics, which limit the recommendation accuracy. On the other hand, it is inefficient to traverse all LBSN data in each recommendation. To solve the above issues, this paper proposes a new location recommendation method LC–G–P, in which, L ouvain method is adopted to cluster users into several communities; and meanwhile, multiple features including G eographical distance, location P opularity are incorporated into location recommendation. Experiments based on real LBSN dataset illustrate that the proposed recommendation scheme LC–G–P has better accuracy and efficiency, in comparison with the existed typical location recommendation schemes.