Results 291 to 300 of about 699,381 (334)

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, 2016
The 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
openaire   +3 more sources

Detecting tip spam in location-based social networks

Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013
Location Based Social Networks (LBSNs) are attracting new users in exponential rates. LBSNs like Foursquare and Gowalla allow users to share their geographic location with friends, search for interesting places as well as posting tips about existing locations. By allowing users to comment on locations, LBSNs increasingly have to deal with a new wave of
Helen Costa, Fabrício Benevenuto, Luiz Henrique de Campos Merschmann   +2 more
openaire   +1 more source

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
openaire   +1 more source

Friendship and mobility: user movement in location-based social networks

Knowledge Discovery and Data Mining, 2011
Eunjoon Cho, Seth A. Myers, J. Leskovec
semanticscholar   +1 more source

SocialTrail:Recommending Social Trajectories from Location-Based Social Networks

2015
Trajectory 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).
Zhang, Qinzhe, Yu, Litao, Long, Guodong
openaire   +2 more sources

Social-Aware KNN Search in Location-Based Social Networks

2014
Location-based social network services have become widely available on mobile devices. It not only helps users to strengthen their social connections, but also provides useful information. An appealing application of using these information is helping users to find proper objects(points of interests) nearby with friends’ visiting experiences.
Huiqi Hu, Jianhua Feng, Sitong Liu, Xuan Zhu   +3 more
openaire   +1 more source

Location-Based Social Networks: Users

2011
In 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
openaire   +1 more source

Trust-aware spatial–temporal feature estimation for next POI recommendation in location-based social networks

Social Network Analysis and Mining, 2023
Malika Acharya, K. Mohbey
semanticscholar   +1 more source

Objectives and State-of-the-Art of Location-Based Social Network Recommender Systems

ACM Computing Surveys, 2018
Zhijun Ding, Xiaolun Li, Changjun Jiang, Mengchu Zhou   +3 more
semanticscholar   +1 more source

Dual Subgraph-Based Graph Neural Network for Friendship Prediction in Location-Based Social Networks

ACM Transactions on Knowledge Discovery From Data, 2023
Xuemei Wei, Yezheng Liu, Jianshan Sun
exaly