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Yannis Theodoridis
Researcher at University of Piraeus
Publications - 236
Citations - 10009
Yannis Theodoridis is an academic researcher from University of Piraeus. The author has contributed to research in topics: Spatial database & Spatial query. The author has an hindex of 47, co-authored 223 publications receiving 9426 citations. Previous affiliations of Yannis Theodoridis include National and Kapodistrian University of Athens & Research Academic Computer Technology Institute.
Papers
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Big data analytics for time critical maritime and aerial mobility forecasting
George A. Vouros,Christos Doulkeridis,Georgios M. Santipantakis,Akrivi Vlachou,Nikos Pelekis,Harris V. Georgiou,Yannis Theodoridis,Kostas Patroumpas,Elias Alevizos,Alexander Artikis,Georg Fuchs,Michael Mock,Gennady Andrienko,Natalia Andrienko,Cyril Ray,Christophe Claramunt,Elena Camossi,A-L. Jousselme,David Scarlatti,Jose Manuel Cordero +19 more
TL;DR: Progress achieved towards time critical big data analytics solutions to user-defined challenges in the air-traffic management and maritime domains and further research challenges concerning data integration and management, predictive analytics for trajectory and events forecasting, and visual analytics are described.
Proceedings ArticleDOI
Sea Area Monitoring and Analysis of Fishing Vessels Activity: The i4sea Big Data Platform
Panagiotis Tampakis,Eva Chondrodima,Aggelos Pikrakis,Yannis Theodoridis,Kostis Pristouris,Harry Nakos,Eleni Petra,Theodore Dalamagas,Andreas Kandiros,Georgios Markakis,I. Maina,Stefanos Kavadas +11 more
TL;DR: The architecture of the i4sea big data platform for sea area monitoring and analysis of fishing vessels activity is presented and the operation of some use-case pilot scenarios is demonstrated.
Proceedings Article
Who Cares about Others' Privacy: Personalized Anonymization of Moving Object Trajectories
TL;DR: This paper proposes efficient modifications to state-of-the-art (k,δ)-anonymization algorithms by introducing a novel technique built upon users’ personalized privacy settings, and utilizes datasetaware trajectory segmentation in order to reduce information distortion.
Book ChapterDOI
Distance Join Queries of Multiple Inputs in Spatial Databases
TL;DR: In this article, the problem of finding the Kn-tuples between n spatial datasets that have the smallest D distance -values, the so-called K-Multi-Way Distance Join Query (K-MWDJQ), is addressed.
Book ChapterDOI
Access Methods for Intervals
TL;DR: This chapter presents classical main-memory solutions to the stabbing query, namely: the Interval Tree, the Segment Tree and the Priority Search Tree, which have been extended in various ways to support intervals in external memory.