Lefteris Stamatogiannakis

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PAROS is a generic system under design whose goal is to offer personalization, recommendation, and other adaptation services to information providing systems. In its heart lies a rich user model able to capture several diverse aspects of user behavior, interests, preferences, and other attitudes. The user model is instantiated with profiles of users, which(More)
In this demonstration, we present a flexible system that enables the provision of personalized functionalities to digital libraries. The system has been developed based on the needs of The European Library portal and will be demonstrated in that particular context, but could be applied more generally. It implements a broad set of data processing, analysis,(More)
Big Data applications require real-time processing of complex computations on streaming and static information. Applications such as the diagnosis of power generating turbines require the integration of high velocity streaming and large volume of static data from multiple sources. In this paper we study various optimisations related to efficiently(More)
Clouds have become an attractive platform for highly scalable processing of Big Data, especially due to the concept of elasticity, which characterizes them. Several languages and systems for cloud-based data processing have been proposed in the past, with the most popular among them being based on MapReduce [7]. In this paper, we present Exareme, a system(More)
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