Results 141 to 150 of about 3,208 (177)

Recommending PO is in LBSNs with Deep Learning

2021 10th Mediterranean Conference on Embedded Computing (MECO), 2021
In recent years, the representation of real-life problems into k-partite graphs introduced a new era in Machine Learning. The combination of virtual and physical layers through Location Based Social Networks (LBSNs) offered a different meaning into the constructed graphs.
openaire   +1 more source

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
openaire   +1 more source

A spatio-temporal network model to represent and analyze LBSNs

2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), 2015
With the increasing popularity of Location-based Social Networks (LBSNs), users have shared information about places they have visited, creating a link between the real world (their movements on the globe) and the virtual world (what they express about these movements on the LBSNs). In this article, we propose the SiST model, which contains information
B N Moreno, V C Times, S Matwin
openaire   +1 more source

Design and Implementation of LBSNS Service Model

2012
Recently, Location Based Service (LBS) is expanding its service areas with the spread of smart phones and is offering more personalized contents according to the variety of needs from customers. Specially, Location Based Social Network Service (LBSNS) is emerging as the most promising service among the applications of LBS.
Youngdo Joo, Younghwa An
openaire   +1 more source

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
openaire   +2 more sources

Measuring user similarity using check-ins from LBSN: a mobile recommendation approach for e-commerce and security services

Enterprise Information Systems, 2019
Social friendship and geographical position information often reflects individuals’ personal preferences and other types of knowledge that can be used to extract their similarity for recommendation systems.
Haidong Zhong, Hongbo Lyu, Shaozhong Zhang, P. Li, Z. Zhang, Li D. Xu   +5 more
semanticscholar   +1 more source

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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Detecting Overlapping Communities in LBSNs with Enhanced Location Privacy

Proceedings of the Third International Symposium on Women in Computing and Informatics, 2015
Location based social network (LBSNs) for instance Facebook places and Twitter provides large amount of data which allows service providers to create several applications like group marketing, friend and location recommendations, trend inquiry etc. Location based social networks does not provide precise communities which enables users to subscribe ...
K. Sreelekshmi, Pretty Babu
openaire   +1 more source

A User Profile Awareness Service Collaborative Recommendation Algorithm Under LBSN Environment

International Journal of Cooperative Information Systems, 2019
Nowadays, location-based social network (LBSN) has become one of the most popular applications with the rapid development of mobile Internet. However, due to the spatial and real-time properties, mobile service recommendation under LBSN environment faces
Mingjun Xin, Lijun Wu, Shunxiang Li
semanticscholar   +1 more source

How Use of Location-Based Social Network (LBSN) Services Contributes to Accumulation of Social Capital

Social Indicators Research, 2016
Kyung-Gook Park, Sehee Han
exaly   +2 more sources