Results 131 to 140 of about 228 (183)

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
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LBSN 2012 workshop report

SIGSPATIAL Special, 2013
The ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN) had its fifth annual meeting on November 6 th , 2012. Held on the opening of the ACM SIGSPATIAL GIS conference in Redondo Beach, California, the one-day LBSN'12 event brought together academic and industry researchers from US, Europe,
Gabriel Ghinita, Jennifer Neville, Shawn Newsam   +2 more
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LBSN 2010 workshop report

SIGSPATIAL Special, 2011
Social networking services have become very popular in recent years, especially among younger people. While many people still sit behind a desktop computer to upload photos, write blogs and communicate with friends in the virtual world, an increasing trend enabled by the development of wireless networks and location sensing technologies is to track and
Xing Xie, Wen-Chih Peng
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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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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, Wei Jeng, Francis Fofie, Konstantinos Pelechrinis, Prashant Krishnamurthy   +4 more
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Feature tendency based location prediction in LBSNs

2016 18th International Conference on Advanced Communication Technology (ICACT), 2016
The development of location-based social networks (LBSNs) has brought in massive users' mobility data, providing an unprecedented opportunity to study human mobile behavior. However, the existing location prediction methods suffer from incompleteness of mobility data and disability of selecting the effective feature.
Zi Xing, Hui Tian, Tu Chen, Jing Zhang
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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, Mohamed F. Mokbel
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LBSN 2009 Workshop Report

SIGSPATIAL Special, 2010
Social networking services have become extremely popular in recent years, especially among young people. However, they are still rooted in the virtual world. People usually need to sit behind a desktop computer to upload photos, write blogs and communicate with friends. The development of wireless networks and location sensing technologies have made it
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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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Detecting overlapping communities in LBSNs by fuzzy subtractive clustering

Social Network Analysis and Mining, 2018
With the increasing popularity of location-based social networks (LBSNs), community detection has emerged as an important and practical issue. One of the main shortcomings of the previous methods is that cluster’s centers have been selected randomly in clustering the communities; therefore, different results are obtained in each execution.
Mohammad Ghane’i-Ostad, Hamed Vahdat-Nejad, Majid Abdolrazzagh-Nezhad   +2 more
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