Results 131 to 140 of about 283 (172)

A model for profit maximization in LBSNs

2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA), 2016
Profit Maximization is the problem of finding an optimal strategy to maximize the expected total profit earned by the end of an influence diffusion process under a given propagation model. In the previous works the strategy of influencing the most profitable (influential) users in a social network in order to start the viral marketing campaign has been
Mahnoosh Fatahi, Farhad Mardukhi
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LBSN-Based Personalized Routes Recommendation

Applied Mechanics and Materials, 2014
In this paper, we present personalized routes recommendation on Location Based Social Network. We model user in both geographical space and semantic space, and define Activity Pattern to describe individual’s personalized character, i.e. individual’s activity regularity.
Li Chao Zhu, Zhi Jun Li, Shou Xu Jiang
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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
Bruno Neiva Moreno, Valéria Cesário Times, Stan Matwin   +2 more
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Understanding Human Dynamics of Check-in Behavior in LBSNs

2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, 2013
With the increase of popularity and pervasive use of sensor-embedded smart phones, location-based social network services (LBSNs) are widely used in recent years. In this paper, we investigate human dynamics of the check-in data crawled from Jie Pang, a famous Chinese LBSN service. We study interval time and jump size (i.e.
Yun Feng, Zhiwen Yu 0001, Xinjiang Lu, Jilei Tian   +3 more
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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

Investigating City Characteristics Based on Community Profiling in LBSNs

2012 Second International Conference on Cloud and Green Computing, 2012
While the detection of social subgroups (i.e., communities) has always been a fundamental task in social network analysis, few efforts has been made to characterize the detected community. Meanwhile, to effectively facilitate applications based on the community structure, it is very important to understand the features of each community.
Zhu Wang 0001, Daqing Zhang 0001, Dingqi Yang, Zhiyong Yu 0001, Xingshe Zhou 0001, Zhiwen Yu 0001   +5 more
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A Personalized Geographic-Based Diffusion Model for Location Recommendations in LBSN

2014 9th Latin American Web Congress, 2014
Location Based Social Networks (LBSN) have emerged with the purpose of allowing users to share their visited locations with their friends. Foursquare, for instance, is a popular LBSN where users endorse and share tips about visited locations. In order to improve the experience of LBSN users, simple recommender services, typically based on geographical ...
Iury Nunes, Leandro Balby Marinho
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A Graph-Based Taxonomy of Recommendation Algorithms and Systems in LBSNs

IEEE Transactions on Knowledge and Data Engineering, 2016
Recently, location-based social networks (LBSNs) gave the opportunity to users to share geo-tagged information along with photos, videos, and SMSs. Recommender systems can exploit this geographic information to provide much more accurate and reliable recommendations to users.
Pavlos Kefalas, Panagiotis Symeonidis, Yannis Manolopoulos   +2 more
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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
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On the Impact of Neighborhood Selection Strategies for Recommender Systems in LBSNs

2017
Location-based social networks (LBSNs) have emerged as a new concept in online social media, due to the widespread adoption of mobile devices and location-based services. LBSNs leverage technologies such as GPS, Web 2.0 and smartphones to allow users to share their locations (check-ins), search for places of interest or POIs (Point of Interest), look ...
Carlos Rios, Silvia N. Schiaffino, Daniela Godoy   +2 more
openaire   +2 more sources