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Mobile social networking middleware: A survey
2013
Pervasive and Mobile Computing
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Indeed, MSN enhances the capabilities of more traditional Online Social Networking (OSN) to a great extent by enabling mobile users to benefit from opportunistically created social communities; these communities ...
The convergence of social networking and mobile computing is expected to generate a new class of applications, called Mobile Social Networking (MSN) applications, that will be of significant importance ...
, e.g., the user focal node in case of a user-centric approach. ...
doi:10.1016/j.pmcj.2013.03.001
fatcat:pvtkbe5unvgjrcupo6inxq4qqe
Social Network Analysis of Mobile Streaming Networks
2016
2016 17th IEEE International Conference on Mobile Data Management (MDM)
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Call data generated from mobile phones reflect a social network structure. Analyzing the topology, behavior and dynamics of such networks is one of the prevailing interests in network science. ...
We also discussed sampling at a precise level of socio-centric and ego-centric network. We delineated and evaluated some sampling methods and algorithms. ...
A family can be people sharing common geographical location. This aspect can be applied to churn prediction in call networks. ...
doi:10.1109/mdm.2016.84
dblp:conf/mdm/Tabassum16
fatcat:va5c5gom7fc7voohloburdb24y
Socially Aware Networking: A Survey
2015
IEEE Systems Journal
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Consequently, today's mobile networks are becoming increasingly human centric. This leads to the emergence of a new field which we call socially-aware networking (SAN). ...
This emerging paradigm is applicable to various types of networks (e.g. opportunistic networks, mobile social networks, delay tolerant networks, ad hoc networks, etc) where the users have social relationships ...
This makes the mobile social learning a vital issue. ...
doi:10.1109/jsyst.2013.2281262
fatcat:5c3c6fmapffy3kvlano4qg2wqi
Privacy Inference Attack Against Users in Online Social Networks: A Literature Review
2021
IEEE Access
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A large amount of privacy information can be inferred from the content and social traces published by users, which leads to the rise of privacy inference technology for users in social networks. ...
Social relationship inference and attribute inference are two basic attacks on users' privacy in social networks. This is the first systematic review of privacy inference attacks in social networks. ...
S Scellato et al. constructed a social graph by visited users in the same place and established a supervised learning location prediction model [58] . ...
doi:10.1109/access.2021.3064208
fatcat:rljfmzrkenfctjpcgpzrpvmume
Prediction of Subscriber Churn Using Social Network Analysis
2013
Bell Labs technical journal
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In this paper, we present a way to address these challenges by developing a new churn prediction algorithm based on a social network analysis of the call graph. ...
We combine this infl uence and other social factors with more traditional metrics and apply machine-learning methods to compute the propensity to churn for individual users. ...
*Trademarks Facebo ok is a trademark of Facebook, Inc. iPhone is a registered trademark of Apple Inc. TreeNet is a registered trademark of Salford Systems. ...
doi:10.1002/bltj.21575
fatcat:kr25mygsvzamxfmonm5ze5vjze
Dynamic Network Selection in Wireless LAN/MAN Heterogeneous Networks
[chapter]
2007
Mobile WiMAX
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A study on the design of a proposed user-centric dynamic network selection strategy is then presented, which includes a comparison between two of the existing intelligent approaches and an in-depth discussion ...
Given the variability of the radio environment properties and user mobility, the availability and characteristics of an access network will change in time and are highly dependent on location. ...
In the case of the user-centric service oriented heterogeneous wireless network setting there is a need for an intelligent user-centric network selection mechanism inbuilt in the mobile device to aid with ...
doi:10.1201/9780849326400.ch11
fatcat:xogg5dmleva4pia5hcp3xa5ppu
Location Analytics for Location-Based Social Networks
[article]
2018
PhD series, Technical Faculty of IT and Design, ˜Aalborg=ålborgœ University
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Acknowledgements
Acknowledgements viii
Conclusion We proposed the problem of predicting future companions in LBSNs, and an efficient, nontrivial solution, COVER; this solution mines geo-social cohorts ...
[4] proposed the first such data based approach to find influential users in a social network. ...
Influential Users in Social Networks. The influence maximization approaches in social networks are generally divided into two main groups. ...
doi:10.5278/vbn.phd.tech.00038
fatcat:wwovvw4mnjbe5fqno7xn4qqo4e
On Preventing Location Attacks for Urban Vehicular Networks
2016
Mobile Information Systems
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The prevalence of global positioning system (GPS) equipped in vehicular networks exposes users' location information to the location-based services. ...
In this paper, we proposed a sophisticated prediction model to predict driver's next location by using a k-order Markov chain-based third-rank tensor representing the partially observed transfer information ...
The location privacy concern does appear not only in mobile social networks, but also in vehicular networks. ...
doi:10.1155/2016/5850670
fatcat:7o7mx4xccbdxdfg5ipvy7nmoq4
Friends Wall: A Semantic-based Friend Recommendation System for Social Networks
2017
IJARCCE
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Present social networking services suggest friends to users based on their social activities, which may not be the most suitable to react a users taste on friend choice in real life. ...
In this project, we present Friendswall, a semanticbased friend recommendation system for social networks, which present friends to users based on their life styles instead of social activities. ...
We specially thank to those who helped us directly-indirectly in completion of this work successfully. ...
doi:10.17148/ijarcce.2017.6598
fatcat:l2p4wjif4naclcpufhmzyrmthu
Network Representation
[chapter]
2020
Representation Learning for Natural Language Processing
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Network representation learning aims to embed the vertexes in a network into low-dimensional dense representations, in which similar vertices in the network should have "close" representations (usually ...
The representations can be used as the feature of vertices and applied to many network study tasks. In this chapter, we will introduce network representation learning algorithms in the past decade. ...
As shown in Fig. 8.7 , a combination of social networking and location-based services is called as Location-Based Social Networks (LBSN). ...
doi:10.1007/978-981-15-5573-2_8
fatcat:2fljfkgpozhudbgqr7tgv45vxi
Decentralized Self-Management of Trust for Mobile Ad Hoc Social Networks
2011
International Journal of Computer Networks & Communications
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The construction of social networks over mobile devices in the events or at locations has emerged as a new network paradigm. ...
A set of simulations is conducted to evaluate our system deployed in a mobile social network in the presence of dishonest users. 2 opportunities, and commercial advertisement systems that recommend reviews ...
This definition of trust encompasses all of the most important social factors in a spontaneous mobile social network. ...
doi:10.5121/ijcnc.2011.3601
fatcat:sz6nr6ptwvapvjrku3go3vargu
Predicting the content dissemination trends by repost behavior modeling in mobile social networks
2014
Journal of Network and Computer Applications
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We try to tackle this issue by exploring approaches to predict the amount of reposts any given post will obtain in Sina Weibo, a well-known mobile social networking service in China. ...
Experimental results over the collected data from Sina Weibo indicate that our method is effective on content diffusion prediction in mobile social networks. ...
In this paper we aim to explore the approaches to model and predict the information diffusion in Sina Weibo, 5 a well-known social networking service (also a promising mobile social networking service) ...
doi:10.1016/j.jnca.2014.01.015
fatcat:m3s32akjtrdk5dxuteooluvnby
Location-Based Social Networks: Users
[chapter]
2011
Computing with Spatial Trajectories
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The inferred similarity represents the strength of connection between two users in a locationbased social network, and can enable friend recommendations and community discovery. ...
In this chapter, we introduce and define the meaning of location-based social network (LBSN) and discuss the research philosophy behind LBSNs from the perspective of users and locations. ...
Networks: Users
Location-Based Social Networks: Users
Location-Based Social Networks: Users
Location-Based Social Networks: Users
Location-Based Social Networks: Users ...
doi:10.1007/978-1-4614-1629-6_8
fatcat:wblv2rposjfijdioqjnnlfluoe
Probabilistic graphical models in modern social network analysis
2015
Social Network Analysis and Mining
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Finally, we conclude with a discussion of challenges and opportunities for PGMs in social networks. ...
Consequently, there is a growing emphasis on mining social networks to extract information for knowledge and discovery. ...
Social network clustering is especially challenging in a dynamic context, e.g. in Mobile Social Networks [70] . ...
doi:10.1007/s13278-015-0289-6
fatcat:ovrlvvfgonhttl65aqt7p3ckqq
Information-centric mobile caching network frameworks and caching optimization: a survey
2017
EURASIP Journal on Wireless Communications and Networking
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In this paper, a brief survey on Information centric mobile caching network architecture and caching optimization is presented, including cache placement in different mobile wireless network architectures ...
Information centric mobile caching network architectures have emerged in Information-Centric Networking as well as mobile cellular and ad-hoc networks deployed with caches. ...
Mobility-aware CaRs are deployed at the edge of the access networks to support user mobility, and track the mobility of users and context information and can predict their future locations [1] . ...
doi:10.1186/s13638-017-0806-6
fatcat:wwf6gctzbzfbhi6elcecbywkam
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