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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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Proceedings ArticleDOI
Clustering Trajectories of Moving Objects in an Uncertain World
TL;DR: This paper proposes an intuitionistic point vector representation of trajectories that encompasses the underlying uncertainty and introduces an effective distance metric to cope with uncertainty in TD clustering.
Proceedings ArticleDOI
Building real-world trajectory warehouses
Gerasimos Marketos,Elias Frentzos,Irene Ntoutsi,Nikos Pelekis,Alessandra Raffaetà,Yannis Theodoridis +5 more
TL;DR: This work investigates how the traditional data cube model is adapted to trajectory warehouses in order to transform raw location data into valuable information.
Book ChapterDOI
Hermes – a framework for location-based data management
TL;DR: The aim of this paper is to demonstrate Hermes, a robust framework capable of aiding a spatio-temporal database developer in modeling, constructing and querying a database with dynamic objects that change location, shape and size, either discretely or continuously in time.
Journal ArticleDOI
Online event recognition from moving vessel trajectories
Kostas Patroumpas,Elias Alevizos,Alexander Artikis,Marios Vodas,Nikos Pelekis,Yannis Theodoridis +5 more
TL;DR: In this article, the authors present a system for online monitoring of maritime activity over streaming positions from numerous vessels sailing at sea, which employs an online tracking module for detecting important changes in the evolving trajectory of each vessel across time, and thus can incrementally retain concise, yet reliable summaries of its recent movement.
Proceedings ArticleDOI
Processing and optimization of multiway spatial joins using R-trees
TL;DR: In this article, the authors propose a multiway spatial join algorithm that combines data originated from more than two relations, and apply systematic search algorithms that exploit R-tree to efficiently guide search, without building temporary indexes or materializing intermediate results.