A
Alexander Artikis
Researcher at University of Piraeus
Publications - 171
Citations - 3537
Alexander Artikis is an academic researcher from University of Piraeus. The author has contributed to research in topics: Event calculus & Complex event processing. The author has an hindex of 35, co-authored 158 publications receiving 3217 citations. Previous affiliations of Alexander Artikis include Imperial College London & Barcelona Supercomputing Center.
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Book ChapterDOI
Being Logical or Going with the Flow? A Comparison of Complex Event Processing Systems
Elias Alevizos,Alexander Artikis +1 more
TL;DR: This paper compares the widely used Esper system which employs a SQL-based language, and RTEC which is a dialect of the Event Calculus.
Journal ArticleDOI
Interactive Extreme: Scale Analytics Towards Battling Cancer
Nikos Giatrakos,Nikos Katzouris,Antonios Deligiannakis,Alexander Artikis,Minos Garofalakis,George Paliouras,Holger Arndt,Raffaele Grasso,Ralf Klinkenberg,Miguel Ponce de Leon,Gian Gaetano Tartaglia,Alfonso Valencia,Dimitrios Zissis +12 more
TL;DR: A synergetic understanding of cancer evolution and the effect of combination drug therapies on the disease is the cornerstone for developing effective personalized treatments, which can radically improve patients' well-being and their quality of (work and social) life.
Proceedings ArticleDOI
How not to drown in a sea of information: An event recognition approach
Elias Alevizos,Alexander Artikis,Kostas Patroumpas,Marios Vodas,Yannis Theodoridis,Nikos Pelekis +5 more
TL;DR: A system for online vessel tracking that performs, as a first step, a high-rate but accurate trajectory compression and to deal with realistic maritime event patterns, seamlessly integrated spatial and temporal reasoning for online event recognition.
Book ChapterDOI
Clinical Decision Support for Active and Healthy Ageing: An Intelligent Monitoring Approach of Daily Living Activities
TL;DR: Accumulated results show that the implementation of the two separate components, i.e. Sensor Data Fusion and Decision Support System, works adequately well and future work suggests ways to combine both components so that more accurate inference results are achieved.
Book ChapterDOI
Parallel Online Learning of Event Definitions
TL;DR: This work presents a version of OLED that allows for parallel, online learning and evaluates the approach on a benchmark activity recognition dataset and shows that it can reduce training times, while achieving super-linear speed-ups on some occasions.