Results 261 to 270 of about 127,551 (298)

Analysis of a Location-Based Social Network

2009 International Conference on Computational Science and Engineering, 2009
Location-based Social Networks (LSNs) allow users to see where their friends are, to search location-tagged contentwithin their social graph, and to meet others nearby. The recent availability of open mobile platforms, such as Apple iPhones and Google Android phones, makes LSNs much more accessible to mobile users.To study how users share their ...
Nan Li, Guanling Chen
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Personalized location recommendation on location-based social networks

Proceedings of the 8th ACM Conference on Recommender systems, 2014
Personalized location recommendation is a special topic of recommendation. It is related to human mobile behavior in the real world regarding various contexts including spatial, temporal, social, and content. The development of this topic is subject to the availability of human mobile data.
Huiji Gao, Jiliang Tang, Huan Liu 0001
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Personalized location recommendation for location-based social networks

2017 IEEE/CIC International Conference on Communications in China (ICCC), 2017
With the development of social networks and wireless communication technology, location-based social networks (LBSNs) are developing rapidly. Personalized location service in location-based social networks can provide users with a new point-of-interest (POI). Compared to traditional recommendation, point-of-interest recommendation integrates the social
Qianfang Xu, Jiachun Wang, Bo Xiao 0006
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Exploring Social Influence on Location-Based Social Networks

2014 IEEE International Conference on Data Mining, 2014
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.
Yu Ting Wen, Po-Ruey Lei, Wen-Chih Peng, Xiaofang Zhou 0001   +3 more
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Location-Based Social Networks

2014
Location-based Social Networks (LBSNs) can be considered as a special Online Social Network (OSN) category. Actually, an LBSN has the same OSN’s properties, but considers location as the core object of its structure. This chapter initially provides some definitions and basic services that are offered by LBSNs, a brief literature review, and two ...
Wang-Chien Lee, Mao Ye
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Location-Based Social Networks: Locations

2011
While chapter 8 studies the research philosophy behind a location-based social network (LBSN) from the point of view of users, this chapter gradually explores the research into LBSNs from the perspective of locations. A series of research topics are presented, with respect to mining the collective social knowledge from many users' GPS trajectories to ...
Yu Zheng, Xing Xie
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Analyzing Location Predictability on Location-Based Social Networks

2014
With 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, Yin Zhu, Xing Xie 0001, Enhong Chen   +3 more
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Venue attacks in location-based social networks

Proceedings of the 1st ACM SIGSPATIAL International Workshop on Privacy in Geographic Information Collection and Analysis, 2014
Location-Based Social Networks (LBSNs), such as Foursquare, Yelp and Facebook Place, have attracted many people, including business owners who use LBSNs to promote their businesses. A physical location is called a venue or a place of interest in an LBSN.
Lei Jin 0003, Hassan Takabi
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Location-Based Influence Maximization in Social Networks

Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, 2015
In this paper, we aim at the product promotion in O2O model and carry out the research of location-based influence maximization on the platform of LBSN. As offline consuming behavior exists under the O2O environment, the traditional online influence diffusion model could not describe the product acceptance accurately.
Tao Zhou, Jiuxin Cao, Bo Liu 0004, Shuai Xu, Ziqing Zhu, Junzhou Luo   +5 more
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Location-Based Social Networks

2012
The ability to gather and manipulate real world contextual data, such as user location, in modern software systems presents opportunities for new and exciting application areas. A key focus among those working in the area of Location-Based services today has been the creation of social networks which allow mobile device users to exchange details of ...
Declan Traynor, Kevin Curran
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