Results 151 to 160 of about 232 (178)

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, Xiao-Tao Jia, Xian-Zhong Xie, Ning Li   +3 more
openaire   +1 more source

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
openaire   +4 more sources

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.
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source

Continuous Geo-Social Group Monitoring in Dynamic LBSNs

IEEE Transactions on Knowledge and Data Engineering, 2022
Huaijie Zhu, Wei Liu 0061, Jian Yin 0001, Libin Zheng 0001, Xin Huang 0001, Jianliang Xu, Wang-Chien Lee   +6 more
openaire   +1 more source

TSFR: Time-aware Semantic-based Friend Recommendation in LBSNs

2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2018
Advances in broadband wireless networks and location sensing technologies have led to the emergence of location-based online social networks (LBSNs) in recent years. Users' passion for sharing locations has attracted much attention to traditional social networks.
Xiaoyan Zhu 0005, Linjie Zhang, Yizhe Huang, Baoming Bai, Jianfeng Ma 0001   +4 more
openaire   +1 more source

UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN

2015
Massive amounts of geo-social data is generated daily. In this paper, we propose UrbanHubble, a location-based predictive analytics tool that entails a broad range of state-of-the-art location prediction and recommendation algorithms. Besides, UrbanHubble consists of a visualization component that depicts the real-time complex interactions of users on ...
Roland Assam, Simon Feiden, Thomas Seidl 0001   +2 more
openaire   +1 more source

MSC-LBSN: Multi-social Context-aware Hypergraph Representation Learning for LBSNs

2022
Trung, Huynh Thanh, Van Vinh, Tong, Nguyen, Tam, Jo, Jun Hyung, Hongzhi Yin, Nguyen Quoc Viet Hung   +5 more
openaire   +1 more source

IAN

Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2021
Liang-yu Chen, Yutong Chen, Young D. Kwon, Youwen Kang, Pan Hui 0001   +4 more
openaire   +1 more source