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Social networks have undergone an explosive growth in recent years. They constitute a central part of users׳ everyday lives as they are used as major tools for the spread of information, ideas and notifications among the members of the network. In this work we investigate the use of location-based social networks as a medium of emergency notification, for efficient dissemination of emergency information...
The wide adoption of Location Based Social Networks along with advances in mobile technology, has brought forth as a core service the analysis of large volumes of location-based data for personalized Point of Interest (POIs) recommendations. The majority of the existing recommendation systems take advantage of Collaborative Filtering, but they fail to exploit the contextual information involved with...
With the advent of mobile networking and the widespread adoption of smartphone devices, a number of location-based services have emerged, where users actively participate by sharing and receiving mobility data. However, the collection and analysis of user mobility data, such as user location information and trajectory data, especially when exploited together with external sources, such as social networks...
Recently, the massive prevalence of mobile devices has led to the development of mobile social sensing systems where humans are enlisted to act as social sensors to perform geo-located tasks that require human intelligence or intervention. Social sensing from ubiquitous users can provide significant benefits particularly during crisis management and emergency scenarios. However, an important problem...
In recent years crowdsourcing systems have shown to provide important benefits to Smartcities, where ubiquitous citizens, acting as mobile human sensors, assist in responding to signals and providing real-time information about city events, to improve the quality of life for businesses and citizens. In this paper we present REquEST, our approach to selecting a small subset of human sensors to perform...
In recent years we have observed a significant increase in the popularity of location-based social networks for exchanging news and experiences, sharing location information, or publishing real world events. One important challenge in such networks is to understand human crowd mobility behavior based on user social activities and interactions. In this paper we introduce PRESENT, our middleware that...
Travel time estimation is a strategically important service in urban environments for personalized and eco-friendly route planning optimization, congestion avoidance, ridesharing and taxi dispatching. However, storing and retrieving traffic data in specific spatiotemporal regions is not an easy task as the data generated by these systems are typically very large and dynamic. In this paper we propose...
Location-based social networks have evolved into powerful tools in recent years. The ability to embed location information in Social Networks such as Facebook, Foursquare and Twitter creates exciting opportunities for users to disseminate and exchange geolocation information in a variety of domains. The problem of exploiting the social ties between the users for maximizing information reach has become...
With the rapid growth of mobile smartphone users, several commercial mobile companies have exploited crowd sourcing as an effective approach to collect and analyze data, to improve their services. In a crowd sourcing system, "human workers" are enlisted to perform small tasks, that are difficult to be automated, in return for some monetary compensation. This paper presents our crowd sourcing...
The proliferation of mobile networking and the increasing capabilities of smartphone devices in the recent years have resulted in transforming mobile smartphone devices into ubiquitous sensing platforms. In this new class of "Community based Participatory Sensing" systems, users actively participate in the data collection and sharing for the benefit of the community, in a wide range of application...
In the recent years we have witnessed a proliferation of distributed stream processing systems that need to operate efficiently, even when data bursts occur. Examples include road traffic networks, processing of financial feeds, network monitoring and real-time sensor data analysis systems. An important challenge in managing these systems is effective resource management and meeting the QoS demands...
In the recent years we are experiencing the rapid growth of crowd sourcing systems, in which "human workers" are enlisted to perform tasks more effectively than computers, and get compensated for the work they provide. The common belief is that the wisdom of the "human crowd" can greatly complement many computer tasks which are assigned to machines. A significant challenge facing...
Over the recent years, the proliferation of mobile networking and the increasing capabilities of smartphone devices have led to the development of “Participatory Sensing” applications, where users actively participate in data collection and sharing in a wide range of application domains from entertainment, to transportation, to environmental monitoring. One important challenge in these settings is...
In the recent years we have witnessed a proliferation of distributed stream processing systems that need to operate under bursty workloads. Examples include road traffic control, processing of financial feeds, network monitoring and real-time sensor data analysis systems. Meeting the QoS requirements of the stream processing systems under burstiness is a challenging process. In this paper we present...
The recent years have seen a proliferation of community sensing or participatory sensing paradigms, where individuals rely on the use of smart and powerful mobile devices to collect, store and analyze data from everyday life. Due to this massive collection of the data, a key challenge to all such developments, is to provide a simple but efficient way to facilitate the programming of distributed applications...
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