Results 161 to 170 of about 687 (209)

Using Visualization to Explore Original and Anonymized LBSN Data

Computer Graphics Forum, 2016
AbstractWe present GSUVis, a visualization tool designed to provide better understanding of location‐based social network (LBSN) data. LBSN data is one of the most important sources of information for transportation, marketing, health, and public safety.
Ebrahim Tarameshloo, M. Hosseinkhani Loorak, Philip W. L. Fong, Sheelagh Carpendale   +3 more
exaly   +3 more sources

Towards multi-dimensional knowledge-aware approach for effective community detection in LBSN

World Wide Web, 2022
In this paper, we focus on the problem of detecting communities, where users have similar characteristics in both social relationship and check-in behavior in location based social network (LBSN).
Yunliang Chen, Ningning Cui
exaly   +1 more source

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Analyzing LBSN Data

Synthesis Lectures on Data Mining and Knowledge Discovery, 2015
Huiji Gao
exaly   +2 more sources

Personalized LBSN Recommendation System

Proceedings of the 2017 International Conference on Management Engineering, Software Engineering and Service Sciences, 2017
To explore deep value of user comments in LBSN, this article through to Foursquare check-in with geography information analysis and review data using AFINN dictionary user comments emotions tend to get user implicit rating for this product. Using the score as the foundation, proposed and implemented an integrated collaborative filtering recommendation ...
Jingling Zhao, Tianyi Wang, Xiaojun Xu, Yu Yang   +3 more
openaire   +1 more source

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.
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Towards reliable spatial information in LBSNs

Proceedings of the 2012 ACM Conference on Ubiquitous Computing, 2012
The proliferation of Location-based Social Networks (LBSNs) has been rapid during the last year due to the number of novel services they can support. The main interaction between users in an LBSN is location sharing, which builds the spatial component of the system.
Ke Zhang 0013, Wei Jeng, Francis Fofie, Konstantinos Pelechrinis, Prashant Krishnamurthy   +4 more
openaire   +1 more source

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
openaire   +1 more source

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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