Advances in big data : proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece

The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspir...

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Bibliographic Details
Corporate Author: International Neural Network Society. Conference on Big Data
Other Authors: Angelov, Plamen P., (Editor), Manolopoulos, Yannis, 1957- (Editor), Iliadis, Lazaros S., (Editor), Roy, Asim, (Editor), Vellasco, Marley Maria B. R., (Editor)
Format: eBook
Language: English
Published: Cham : Springer, [2017]
Series: Advances in intelligent systems and computing ; 529.
Subjects:
ISBN: 9783319478982
9783319478975
Physical Description: 1 online resource : illustrations (chiefly color)

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Table of contents

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110 2 |a International Neural Network Society.  |b Conference on Big Data  |n (2nd :  |d 2016 :  |c Thessalonike, Greece) 
245 1 0 |a Advances in big data :  |b proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece /  |c Plamen Angelov, Yannis Manolopoulos, Lazaros Iliadis, Asim Roy, Marley Vellasco, editors. 
264 1 |a Cham :  |b Springer,  |c [2017] 
264 4 |c ©2017 
300 |a 1 online resource :  |b illustrations (chiefly color) 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a Advances in intelligent systems and computing,  |x 2194-5357 ;  |v 529 
500 |a International conference proceedings. 
504 |a Includes bibliographical references and index. 
505 0 |a Predicting human behavior based on web search activity: Greek referendum of 2015 -- Compact Video Description and Representation for Automated Summarization of Human Activities -- Attribute Learning for Network Intrusion Detection -- A Fast Deep Convolutional Neural Network for face detection in Big Visual Data -- Learning Symbols by Neural Network -- Designing HMMs models in the age of Big Data -- Extended Formulations for Online Action Selection on Big Action Sets -- Multi-Task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports -- An infrastructure and approach for infering knowledge over Big Data in the Vehicle Insurance Industry -- Unified Retrieval Model of Big Data -- Adaptive Elitist Differential Evolution Extreme Learning Machines on Big Data: Intelligent Recognition of Invasive Species. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23-25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Big data  |v Congresses. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Angelov, Plamen P.,  |e editor. 
700 1 |a Manolopoulos, Yannis,  |d 1957-  |e editor. 
700 1 |a Iliadis, Lazaros S.,  |e editor. 
700 1 |a Roy, Asim,  |e editor. 
700 1 |a Vellasco, Marley Maria B. R.,  |e editor. 
776 0 8 |i Print version:  |t Advances in big data.  |d Cham : Springer, [2017]  |z 9783319478975  |w (OCoLC)961100816 
830 0 |a Advances in intelligent systems and computing ;  |v 529. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-47898-2  |y Plný text 
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999 |c 99473  |d 99473 
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