Social network services for innovative smart cities: the RADICAL platform approach

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Fotis Aisopos ◽  
Antonios Litke ◽  
Magdalini Kardara ◽  
Konstantinos Tserpes ◽  
Pablo Martínez Campo ◽  
...  
Keyword(s):  
Social Network ◽  
Internet Of Things ◽  
Large Scale ◽  
Smart Cities ◽  
Network Services ◽  
Cloud Environment ◽  
Living Labs ◽  
Social Network Services ◽  
Smart Governance ◽  
Radical Approach

In this paper we present the RADICAL platform, a software stack that enables the combination of social network (SN) services and Internet of Things (IoT) in the context of innovative smart cities. RADICAL makes possible the development and deployment of interoperable pervasive multi-sensory and socially-aware services; facilitates smart governance and flexible replication of services across cities and regions through a Virtual Machine generation mechan-ism in a sophisticated cloud environment. A large scale piloting of the platform integrates, deploys and tests various services in the areas of Cycling Safety, Participatory Urbanism, Augmented Reality and others while a large group of citizens from different countries are actively involved in the co-creation, validation and evaluation of the RADICAL approach on the basis of an innovative Living Labs approach.

Incremental face recognition for large-scale social network services

2012 ◽  
Vol 45 (8) ◽  
pp. 2868-2883 ◽  
Author(s):  
Kwontaeg Choi ◽  
Kar-Ann Toh ◽  
Hyeran Byun
Keyword(s):  
Social Network ◽  
Face Recognition ◽  
Large Scale ◽  
Network Services ◽  
Social Network Services

scholarly journals An Information Recommendation Technique Based on Influence and Activeness of Users in Social Networks

2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Recommendation Systems ◽  
Network Services ◽  
The Past ◽  
User Behaviors ◽  
User Influence ◽  
User Activity ◽  
Information Recommendation ◽  
Social Network Services

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.

Face hallucination and recognition in social network services

2014 ◽  
Vol 71 (6) ◽  
pp. 2035-2049 ◽  
Author(s):  
Feng Jiang ◽  
Seungmin Rho ◽  
Bo-Wei Chen ◽  
Xiaodan Du ◽  
Debin Zhao
Keyword(s):  
Social Network ◽  
Network Services ◽  
Face Hallucination ◽  
Social Network Services
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