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Fatemeh Ghanaati, Gholamhossein Ekbatanifard and Kamrad Khoshhal Roudposhti
In recent years, next location prediction has been of paramount importance for a wide range of location-based social network (LBSN) services. The influence of geographical and temporal contextual information (GTCI) is crucial for analyzing individual beh...
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Shuqiang Xu, Qunying Huang and Zhiqiang Zou
Location-based social networks (LBSN) allow users to socialize with friends by sharing their daily life experiences online. In particular, a large amount of check-ins data generated by LBSNs capture the visit locations of users and open a new line of res...
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Eric Hsueh-Chan Lu and You-Ru Lin
With the rise in the Internet of Things (IOT), mobile devices and Location-Based Social Network (LBSN), abundant trajectory data have made research on location prediction more popular. The check-in data shared through LBSN hide information related to lif...
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Yan Zhou, Kaixuan Zhou and Shuaixian Chen
The rapid development of big data technology and mobile intelligent devices has led to the development of location-based social networks (LBSNs). To understand users? behavioral patterns and improve the accuracy of location-based services, point-of-inter...
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Dongjin Yu, Yi Shen, Kaihui Xu and Yihang Xu
Point-Of-Interest (POI) recommendation not only assists users to find their preferred places, but also helps businesses to attract potential customers. Recent studies have proposed many approaches to the POI recommendation. However, the lack of negative ...
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Yi-Chung Chen, Hsi-Ho Huang, Sheng-Min Chiu and Chiang Lee
Joint promotion is a valuable business strategy that enables companies to attract more customers at lower operational cost. However, finding a suitable partner can be extremely difficult. Conventionally, one of the most common approaches is to conduct su...
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Álvaro Bernabeu-Bautista, Leticia Serrano-Estrada, V. Raul Perez-Sanchez and Pablo Martí
This research sheds light on the relationship between the presence of location-based social network (LBSN) data and other economic and demographic variables in the city of Valencia (Spain). For that purpose, a comparison is made between location patterns...
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Hang Zhang, Mingxin Gan and Xi Sun
In location-based social networks (LBSNs), point-of-interest (POI) recommendations facilitate access to information for people by recommending attractive locations they have not previously visited. Check-in data and various contextual factors are widely ...
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Muhammad Rizwan, Wanggen Wan and Luc Gwiazdzinski
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Naimat Ullah Khan, Wanggen Wan and Shui Yu
The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories. This ar...
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