Panagiotis Tampakis

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During the last decade, the domain of mobility data mining has emerged providing many effective methods for the discovery of intuitive patterns representing collective behavior of trajectories of moving objects. Although a few real-world trajectory datasets have been made available recently, these are not sufficient for experimentally evaluating the various(More)
During the past few decades, a number of effective methods for indexing, query processing, and knowledge discovery in moving object databases have been proposed. An interesting research direction that has recently emerged handles semantics of movement instead of raw spatio-temporal data. Semantic annotations, such as “stop,” “move,”(More)
The domain of trajectory data management and mining undoubtedly contributes with interesting research problems and corresponding effective solutions to what is called data science. An interesting trend that poses new challenges in the field and has emerged especially due to the advance of location-based social networks, is that involved data cannot be(More)
In this paper, we present the overall architecture of RoadRunner, a Hadoop-based framework that enhances the efficiency of rank-aware query processing by introducing various optimizations to Hadoop, without changing its internal operation. RoadRunner focuses on a specific class of queries that involve ranking, such as top-k queries and top-k joins, as well(More)
Acknowledgements I would like to thank Yannis Theodoridis and Nikos Pelekis for their insight-ful supervision during the writing of my thesis. I would also like to thank my colleagues Despina Kopanaki, Panagiotis Tampakis, Nikos Giatrakos, Stelios Sideridis, Giannis Kostis, and Michalis Basios for our cooperation in the lab. Last but not least, I would like(More)
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