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Panagiotis Karamolegkos, Argyro Mavrogiorgou, Athanasios Kiourtis and Dimosthenis Kyriazis
Big Data is a phenomenon that affects today?s world, with new data being generated every second. Today?s enterprises face major challenges from the increasingly diverse data, as well as from indexing, searching, and analyzing such enormous amounts of dat...
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D.E. Savitsky,M.E. Dunaev,K.S. Zaytsev
Pág. 70 - 76
The purpose of this work is to study methods for detecting anomalies in the processing of data streams in distributed streams in real time. To do this, the authors carried out a modification of the K-Means algorithm, called K-Means in real time, and carr...
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Athanasios Alexopoulos, Georgios Drakopoulos, Andreas Kanavos, Phivos Mylonas and Gerasimos Vonitsanos
At the dawn of the 10V or big data data era, there are a considerable number of sources such as smart phones, IoT devices, social media, smart city sensors, as well as the health care system, all of which constitute but a small portion of the data lakes ...
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Tamas Foldi, Chris von Csefalvay and Nicolas A. Perez
The new barrier mode in Apache Spark allows for embedding distributed deep learning training as a Spark stage to simplify the distributed training workflow. In Spark, a task in a stage does not depend on any other tasks in the same stage, and hence it ca...
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Mounir Hafsa and Farah Jemili
Cybersecurity ventures expect that cyber-attack damage costs will rise to $11.5 billion in 2019 and that a business will fall victim to a cyber-attack every 14 seconds. Notice here that the time frame for such an event is seconds. With petabytes of data ...
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