Results 171 to 180 of about 817 (198)

Genetic Location-Based Social Networks (G-LBSN)

Proceedings of the 3rd International Workshop on Location and the Web, 2010
Despite much advances in both general and targeted Social Network Services (SNS) and Location-Based Social Networks (LBSN), there is currently a void in literatures on SNS that form temporary social networks to address specific problems and employ intelligent classification of members and coordination of tasks toward goal oriented action.
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Community Detection and Location Recommendation Based on LBSN

2017 International Conference on Network and Information Systems for Computers (ICNISC), 2017
Community detection is an effective tool for mining hidden information in social networks. Label propagation is a widely used and effective community detection algorithm. A lot of work has been done based on label propagation for standalone machine computing. While in location based social networks (LBSN), paralleled label propagation is needed to deal
Chang Su
exaly   +2 more sources

NationTelescope: Monitoring and visualizing large-scale collective behavior in LBSNs

Journal of Network and Computer Applications, 2015
The research of collective behavior has attracted a lot of attention in recent years, which can empower various applications, such as recommendation systems and intelligent transportation systems. However, in traditional social science, it is practically difficult to collect large-scale user behavior data.
Yang, Dingqi, Zhang, Daqing, Chen, Longbiao, Qu, Bingqing   +3 more
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Multi-task Learning of Heterogeneous Hypergraph Representations in LBSNs

Location-based service networks (LBSNs) have emerged as a primary source for numerous applications that attempt to understand human mobility and analyze social networks. However, mainstream studies on representation learning often consider LBSNs to be either regular graphs or a mixture of regular graphs and hypergraphs.
Dong Duc Anh Nguyen, Minh Hieu Nguyen 0003, Phi Le Nguyen, Jun Jo 0001, Hongzhi Yin, Thanh Tam Nguyen   +5 more
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A Spatial-Temporal Topic Model for the Semantic Annotation of POIs in LBSNs

ACM Transactions on Intelligent Systems and Technology, 2016
Semantic tags of points of interest (POIs) are a crucial prerequisite for location search, recommendation services, and data cleaning. However, most POIs in location-based social networks (LBSNs) are either tag-missing or tag-incomplete. This article aims to develop semantic annotation techniques to automatically infer tags for POIs.
Tieke He, Hongzhi Yin, Zhenyu Chen 0001, Xiaofang Zhou 0001, Shazia Sadiq, Bin Luo 0003   +5 more
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LBSN Data and the Social Butterfly Effect (Vision Paper)

Proceedings of the 8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, 2015
LBSN data are well-suited for research questions and perspectives on social or spatial phenomena. Researchers often subset large LBSN datasets into different social networks (using snowball sampling), temporal or spatial granularities, to test for statistical patterns.
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LBSN 2011 Workshop Report: the Third ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN 2011)

SIGSPATIAL Special, 2012
Social networks have been prevalent on the Internet, attracting many professionals from a variety of fields. By adding a location dimension, we can bring online social networks back to the physical world and share our real-life experiences in the virtual world conveniently.
Yu Zheng 0004, Mohamed F. Mokbel
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Personalized POI Recommendation Model in LBSNs

2017
The development of location-based social networks (LBSNs) generates large volume of check-in data. Point-of-interest recommendation (POI) is important for users to find some attractive venues, sometimes when users are in some places far away from their living cities.
Zhong Guo, Ma Changyi
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Friendship Prediction Based on the Fusion of Topology and Geographical Features in LBSN

2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013
Friendship prediction in social networks is useful for various applications, such as friend/place recommendation and privacy management. In this paper, we propose a friendship prediction approach by fusing the topology and geographical features in location based social networks (LBSNs). We investigate the features of users' relationship both online and
Hui Luo, Bin Guo 0001, Zhiwen Yu 0001, Zhu Wang 0001, Yun Feng   +4 more
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GeoLifecycle

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2019
As Location-Based Social Networks (LBSNs) have become widely used by users, understanding user engagement and predicting user churn are essential to the maintainability of the services. In this work, we conduct a quantitative analysis to understand user engagement patterns exhibited both offline and online in LBSNs.
Kwon, Young Dae, Chatzopoulos, Dimitrios, Haq, Ehsan-ul, Wong, Chi Wing, Hui, Pan   +4 more
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