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Adaptive location recommendation algorithm based on location-based social networks
2015 10th International Conference on Computer Science & Education (ICCSE), 2015With the development of social network and location-based services, location-based social network rose. In the Geo-Social recommended system, location recommendation has become a focus of recent research. This paper analyzes three questions the personalized recommendation algorithm may face: location data sparseness, cold start and registered locations
Kunhui Lin +4 more
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Extracting urban patterns from location-based social networks
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks, 2011Social networks attract lots of new users every day and absorb from them information about events and facts happening in the real world. The exploitation of this information can help identifying mobility patterns that occur in an urban environment as well as produce services to take advantage of social commonalities between people. In this paper we set
FERRARI, Laura +3 more
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Analyzing Location Predictability on Location-Based Social Networks
2014With the growing popularity of location-based social networks, vast amount of user check-in histories have been accumulated. Based on such historical data, predicting a user’s next check-in place is of much interest recently. There is, however, little study on the limit of predictability of this task and its correlation with users’ demographics.
Defu Lian +3 more
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Exploring Social Influence on Location-Based Social Networks
2014 IEEE International Conference on Data Mining, 2014Recently, 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.
Yu-Ting Wen +3 more
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Enhancing opportunistic networking using location based social networks
Proceedings of the 8th ACM International Workshop on Hot Topics in Planet-scale mObile computing and online Social neTworking, 2016The wireless communication capabilities of mobile devices have evolved rapidly during the last decade. Exploiting the various connectivity technologies available devices are capable of forming intermittently connected networks; in these networks, defined as Mobile Opportunistic Networks (MONs), a multitude of mobile devices are carried by people and ...
Lambrinos, Lambros, Kosmides, Pavlos
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Location-Based Social Networks: Users
2011In this chapter, we introduce and define the meaning of location-based social network (LBSN) and discuss the research philosophy behind LBSNs from the perspective of users and locations. Under the circumstances of trajectory-centric LBSN, we then explore two fundamental research points concerned with understanding users in terms of their locations. One
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A Location Recommender System for Location-Based Social Networks
2014 International Conference on Mathematics and Computers in Sciences and in Industry, 2014Location-Based Social media have evolved rapidly during the last decade. Most Social Networks provide a plethora of venues and points of interest, while at the same time, users are able to declare their presence in specific locations (a process often referred to as "check-ins"), to provide ratings about the visited places or even suggest them to their ...
Pavlos Kosmides +5 more
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SocialTrail:Recommending Social Trajectories from Location-Based Social Networks
2015Trajectory recommendation plays an important role for travel planning. Most existing systems are mainly designed for spot recommendation without the understanding of the overall trip and tend to utilize homogeneous data only (e.g., geo-tagged images).
Qinzhe Zhang, Litao Yu, Guodong Long
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Multi-location Influence Maximization in Location-Based Social Networks
2018With the development of location-based social networks (LBSNs), location property has been gradually integrated into the influence maximization problem, the key point of which is to bring the users in social networks (online phase) to the product locations for consuming in the real world (offline phase).
Zhen Zhang +3 more
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Social determinants of health and US cancer screening interventions: A systematic review
Ca-A Cancer Journal for Clinicians, 2023Ariella R Korn
exaly