東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Cognitive computing for big data sys...

Sangaiah, Arun Kumar.

Linked to FindBook

Google Book

Amazon

博客來

Cognitive computing for big data systems over IoT = frameworks, tools and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Cognitive computing for big data systems over IoT/ edited by Arun Kumar Sangaiah, Arunkumar Thangavelu, Venkatesan Meenakshi Sundaram.
Reminder of title:	frameworks, tools and applications /
other author:	Sangaiah, Arun Kumar.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	xvi, 375 p. :ill., digital ;24 cm.
[NT 15003449]:	Beyond Automation: The Cognitive IoT - Artificial Intelligence Brings Sense to the Internet of Things -- Cybercrimes Investigation and Intrusion Detection in Internet of Things Based on Data Science Methods -- Modeling and Analysis of Multi-Objective Service Selection Scheme in IoT-Cloud Environment -- Cognitive data science automatic fraud detection solution, based on Benford' s law, fuzzy logic with elements of machine learning -- Reliable Cross Layer Design for E-health Applications - IoT Perspective -- Erasure Codes for Reliable Communication in Internet-ofThings (IoT) embedded with Wireless Sensors -- Review: Security and Privacy Issues of Fog Computing -- A Review on Security and Privacy Challenges of Big Data -- Recent Developments in Deep Learning with Applications -- High-Level Knowledge Representation and Reasoning in a Cognitive IoT/WoT Context -- Applications of IoT in Healthcare -- Security Stipulations on IoT Networks -- A Hyper Heuristic Localization Based Cloned Node Detection Technique using GSA Based Simulated Annealing in Sensor Networks -- Review on Analysis of the Application Areas and Algorithms used in Data Wrangling in Big Data -- An innovation model for Smart Traffic Management System Using Internet of Things(IoT)
Contained By:	Springer eBooks
Subject:	Big data. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-70688-7
ISBN:	9783319706887

Cognitive computing for big data systems over IoT = frameworks, tools and applications /
Cognitive computing for big data systems over IoTframeworks, tools and applications /[electronic resource] :edited by Arun Kumar Sangaiah, Arunkumar Thangavelu, Venkatesan Meenakshi Sundaram. - Cham :Springer International Publishing :2018. - xvi, 375 p. :ill., digital ;24 cm. - Lecture notes on data engineering and communications technologies,v.142367-4512 ;. - Lecture notes on data engineering and communications technologies ;v.14..

Beyond Automation: The Cognitive IoT - Artificial Intelligence Brings Sense to the Internet of Things -- Cybercrimes Investigation and Intrusion Detection in Internet of Things Based on Data Science Methods -- Modeling and Analysis of Multi-Objective Service Selection Scheme in IoT-Cloud Environment -- Cognitive data science automatic fraud detection solution, based on Benford' s law, fuzzy logic with elements of machine learning -- Reliable Cross Layer Design for E-health Applications - IoT Perspective -- Erasure Codes for Reliable Communication in Internet-ofThings (IoT) embedded with Wireless Sensors -- Review: Security and Privacy Issues of Fog Computing -- A Review on Security and Privacy Challenges of Big Data -- Recent Developments in Deep Learning with Applications -- High-Level Knowledge Representation and Reasoning in a Cognitive IoT/WoT Context -- Applications of IoT in Healthcare -- Security Stipulations on IoT Networks -- A Hyper Heuristic Localization Based Cloned Node Detection Technique using GSA Based Simulated Annealing in Sensor Networks -- Review on Analysis of the Application Areas and Algorithms used in Data Wrangling in Big Data -- An innovation model for Smart Traffic Management System Using Internet of Things(IoT)

This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT) It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.

ISBN: 9783319706887

Standard No.: 10.1007/978-3-319-70688-7doiSubjects--Topical Terms:

2045508
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Cognitive computing for big data systems over IoT = frameworks, tools and applications /
LDR:03822nmm a2200325 a 4500 001 2132841
003 DE-He213
005 20180808111412.0
006 m d
007 cr nn 008maaau
008 181005s2018 gw s 0 eng d
020 $a 9783319706887 $q (electronic bk.)
020 $a 9783319706870 $q (paper)
024 7 $a 10.1007/978-3-319-70688-7 $2 doi
035 $a 978-3-319-70688-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.B45
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 005.7 $2 23
090 $a QA76.9.B45 $b C676 2018
245 0 0 $a Cognitive computing for big data systems over IoT $h [electronic resource] : $b frameworks, tools and applications / $c edited by Arun Kumar Sangaiah, Arunkumar Thangavelu, Venkatesan Meenakshi Sundaram.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xvi, 375 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes on data engineering and communications technologies, $x 2367-4512 ; $v v.14
505 0 $a Beyond Automation: The Cognitive IoT - Artificial Intelligence Brings Sense to the Internet of Things -- Cybercrimes Investigation and Intrusion Detection in Internet of Things Based on Data Science Methods -- Modeling and Analysis of Multi-Objective Service Selection Scheme in IoT-Cloud Environment -- Cognitive data science automatic fraud detection solution, based on Benford' s law, fuzzy logic with elements of machine learning -- Reliable Cross Layer Design for E-health Applications - IoT Perspective -- Erasure Codes for Reliable Communication in Internet-ofThings (IoT) embedded with Wireless Sensors -- Review: Security and Privacy Issues of Fog Computing -- A Review on Security and Privacy Challenges of Big Data -- Recent Developments in Deep Learning with Applications -- High-Level Knowledge Representation and Reasoning in a Cognitive IoT/WoT Context -- Applications of IoT in Healthcare -- Security Stipulations on IoT Networks -- A Hyper Heuristic Localization Based Cloned Node Detection Technique using GSA Based Simulated Annealing in Sensor Networks -- Review on Analysis of the Application Areas and Algorithms used in Data Wrangling in Big Data -- An innovation model for Smart Traffic Management System Using Internet of Things(IoT)
520 $a This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT) It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.
650 0 $a Big data. $3 2045508
650 0 $a Data mining. $3 562972
650 0 $a Information storage and retrieval systems. $3 576262
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
700 1 $a Sangaiah, Arun Kumar. $3 3227119
700 1 $a Thangavelu, Arunkumar. $3 3299737
700 1 $a Meenakshi Sundaram, Venkatesan. $3 3299738
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Lecture notes on data engineering and communications technologies ; $v v.14. $3 3299739
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-70688-7
950 $a Engineering (Springer-11647)