SPEEDD

Jan 1, 2016
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SPEEDD developed a prototype for proactive event-driven decision-making wherein decisions are triggered by forecasting events. The decisions are in real-time and require on-the-fly processing of large amounts of noisy data flooding in from various geographical locations, and historical data.

Traffic Management Fraud Management
Evangelos Michelioudakis
Evangelos Michelioudakis
Data Scientist

My research interests include artificial intelligence and machine learning.

Publications

OSL𝛼: Online Structure Learning Using Background Knowledge Axiomatization
We present OSLα — an online structure learner for Markov Logic Networks (MLNs) that exploits background knowledge axiomatization in …
E. Michelioudakis, A. Skarlatidis, G. Paliouras, A. Artikis
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Online Structure Learning for Traffic Management
Most event recognition approaches in sensor environments are based on manually constructed patterns for detecting events, and lack the …
E. Michelioudakis, A. Artikis, G. Paliouras
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