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20231027140348.0 |
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200225t20202020enka ob 001 0 eng d |
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|a YDX
|b eng
|e rda
|e pn
|c YDX
|d OCLCQ
|d YDXIT
|d CUS
|d OCLCF
|d UKBTH
|d N$T
|d OCLCO
|d K6U
|d OCLCQ
|d OCLCO
|d OCLCQ
|d OCLCA
|d OCLCO
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020 |
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|a 1785619225
|q (electronic book)
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|a 9781785619229
|q (electronic bk.)
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|z 1785619217
|q (hardcover)
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|z 9781785619212
|q (hardcover)
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|a AU@
|b 000066984841
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|a (OCoLC)1141662021
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|a TK5105.5
|b .T37 2020
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0 |
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|a 621.3981
|2 23
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|a UAMI
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1 |
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|a Tari, Zahir,
|d 1961-
|e author.
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1 |
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|a Network classification for traffic management :
|b anomaly detection, feature selection, clustering and classification /
|c Zahir Tari, Adil Fahad, Abdulmohsen Almalawi and Xun Yi.
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|a Stevenage :
|b Institution of Engineering and Technology,
|c 2020.
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|c ©2020
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|a 1 online resource :
|b illustrations
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|a text
|b txt
|2 rdacontent
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|a still image
|b sti
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a IET computing series ;
|v volume 32
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|a Includes bibliographical references and index (pages 261-268).
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|a Introduction -- Background -- Related work -- A taxonomy and empirical analysis of clustering algorithms for traffic classification -- Toward an efficient and accurate unsupervised feature selection -- Optimizing feature selection to improve transport layer statistics quality -- Optimality and stability of feature set for traffic classification -- A privacy-perserving framework for traffic data publishing -- A semi-supervised approach for network traffic labeling -- A hybrid clustering-classification for accurate and efficient network classification -- Conclusion.
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|a Online resource; title from digital title page (viewed on June 01, 2020).
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|a The book investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. It deals with the following subjects: traffic management; anomaly detection; clustering algorithms; unsupervised feature selection; transport layer statistics quality; feature set; privacy preserving framework for traffic data publishing; semi-supervised approach for network traffic labelling; and hybrid clustering-classification.
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590 |
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|a Knovel
|b ACADEMIC - Software Engineering
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590 |
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|a Knovel
|b ACADEMIC - Computer Hardware Engineering
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|a Telecommunication
|x Traffic
|x Management.
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|a Computer network protocols
|x Management.
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650 |
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6 |
|a Télécommunications
|x Trafic
|x Gestion.
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650 |
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|a Protocoles de réseaux d'ordinateurs
|x Gestion.
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650 |
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7 |
|a Telecommunication
|x Traffic
|x Management
|2 fast
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|a computer network management.
|2 inspect
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|a computer network security.
|2 inspect
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|a data privacy.
|2 inspect
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|a feature selection.
|2 inspect
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|a learning (artificial intelligence)
|2 inspect
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|a pattern classification.
|2 inspect
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|a pattern clustering.
|2 inspect
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|a telecommunication traffic.
|2 inspect
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1 |
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|a Fahad, Adil,
|e author.
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700 |
1 |
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|a Almalawi, Abdulmohsen,
|e author.
|
700 |
1 |
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|a Yi, Xun
|c (College teacher),
|e author.
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776 |
0 |
8 |
|i Print version:
|t NETWORK CLASSIFICATION FOR TRAFFIC MANAGEMENT.
|d [Place of publication not identified] INST OF ENGIN AND TECH, 2020
|z 1785619217
|w (OCoLC)1111784634
|
830 |
|
0 |
|a IET computing series ;
|v 32.
|
856 |
4 |
0 |
|u https://appknovel.uam.elogim.com/kn/resources/kpNCTMADF1/toc
|z Texto completo
|
938 |
|
|
|a EBSCOhost
|b EBSC
|n 2375432
|
938 |
|
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|a YBP Library Services
|b YANK
|n 301114403
|
994 |
|
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|a 92
|b IZTAP
|