Results 271 to 280 of about 231,718 (305)

Location-Based Emerging Event Detection in Social Networks

2013
This paper proposes a system for the early detection of emerging events by grouping micro-blog messages into events and using the message-mentioned locations to identify the locations of events. In our research we correlate user locations with event locations in order to identify the strong correlations between locations and events that are emerging ...
Sayan Unankard, Xue Li 0001, Mohamed A. Sharaf   +2 more
openaire   +2 more sources

Evaluating geo-social influence in location-based social networks

Proceedings of the 21st ACM international conference on Information and knowledge management, 2012
The emerging location-based social network (LBSN) services not only allow people to maintain cyber links with their friends, but also enable them to share the events happening on them at different locations. The geo-social correlations among event participants make it possible to quantify mutual user influence for various events.
Chao Zhang 0014, Lidan Shou, Ke Chen 0005, Gang Chen 0001, Yijun Bei   +4 more
openaire   +1 more source

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

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 location recommendation in location-based social networks: A graph-based approach

Expert Systems With Applications, 2023
Deniz Cantürk, Sang-Wook Kim, Ismail Hakki Toroslu   +2 more
exaly  

Location-based Fast Recommendation Social Network

Proceedings of the 5th International Workshop on Software Knowledge, 2014
Iaakov Exman, Erez Nagar
openaire   +1 more source