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Efficient big data analysis on a single machine using apache spark and self-organizing map libraries

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Autor
Andresic D., Saloun P., Anagnostopoulos I.
Fecha
2017
Language
en
DOI
10.1109/SMAP.2017.8022657
Materia
Conformal mapping
Data handling
Information analysis
Self organizing maps
Semantics
Social networking (online)
Computer clusters
Computer memory
Innovative approaches
Sentiment analysis
Single computer
Single- machines
Software libraries
Stock exchange
Big data
Institute of Electrical and Electronics Engineers Inc.
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Resumen
Apache Spark is commonly used as a big data analytical platform on powerful computer clusters, as it primarily employ the main computer memory for the evaluation. Our attempt adds self-organizing map software libraries onto a single big data analytical stack and is efficient and fast enough even on a standard single computer. This innovative approach brings the big data analysis to researchers with limited resources. Our genuine idea was experimentally confirmed and is described here. As a case study for our method we we used the available #Brexit data and the sentiment analysis of corresponding tweets and the correlation with the stock exchange data. © 2017 IEEE.
URI
http://hdl.handle.net/11615/70576
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