Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/276491
Title: Cognitive Computing for Big Data Systems Over IoT
Other Titles: Frameworks, Tools and Applications /
Authors: Sangaiah, Arun Kumar. ;;Thangavelu, Arunkumar. ;;Meenakshi Sundaram, Venkatesan. ;
subject: Engineering;Data Mining;Computational Intelligence;Engineering;Computational Intelligence;Data Mining and Knowledge Discovery
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Lecture Notes on Data Engineering and Communications Technologies, ; 2367-4512 ; ; 14. ;
Lecture Notes on Data Engineering and Communications Technologies, ; 2367-4512 ; ; 14. ;
Abstract: 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. ;
Description: Printed edition: ; 9783319706870. ;
Q342 ;



No author
No author
URI: http://localhost/handle/Hannan/276491
ISBN: 9783319706887 ;
9783319706870 (print) ;
More Information: XVI, 375 p. 81 illus., 51 illus. in color. ; online resource. ;
Appears in Collections:General Science

Files in This Item:
File SizeFormat 
9783319706887.pdf8.07 MBAdobe PDF
Title: Cognitive Computing for Big Data Systems Over IoT
Other Titles: Frameworks, Tools and Applications /
Authors: Sangaiah, Arun Kumar. ;;Thangavelu, Arunkumar. ;;Meenakshi Sundaram, Venkatesan. ;
subject: Engineering;Data Mining;Computational Intelligence;Engineering;Computational Intelligence;Data Mining and Knowledge Discovery
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Lecture Notes on Data Engineering and Communications Technologies, ; 2367-4512 ; ; 14. ;
Lecture Notes on Data Engineering and Communications Technologies, ; 2367-4512 ; ; 14. ;
Abstract: 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. ;
Description: Printed edition: ; 9783319706870. ;
Q342 ;



No author
No author
URI: http://localhost/handle/Hannan/276491
ISBN: 9783319706887 ;
9783319706870 (print) ;
More Information: XVI, 375 p. 81 illus., 51 illus. in color. ; online resource. ;
Appears in Collections:General Science

Files in This Item:
File SizeFormat 
9783319706887.pdf8.07 MBAdobe PDF
Title: Cognitive Computing for Big Data Systems Over IoT
Other Titles: Frameworks, Tools and Applications /
Authors: Sangaiah, Arun Kumar. ;;Thangavelu, Arunkumar. ;;Meenakshi Sundaram, Venkatesan. ;
subject: Engineering;Data Mining;Computational Intelligence;Engineering;Computational Intelligence;Data Mining and Knowledge Discovery
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Series/Report no.: Lecture Notes on Data Engineering and Communications Technologies, ; 2367-4512 ; ; 14. ;
Lecture Notes on Data Engineering and Communications Technologies, ; 2367-4512 ; ; 14. ;
Abstract: 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. ;
Description: Printed edition: ; 9783319706870. ;
Q342 ;



No author
No author
URI: http://localhost/handle/Hannan/276491
ISBN: 9783319706887 ;
9783319706870 (print) ;
More Information: XVI, 375 p. 81 illus., 51 illus. in color. ; online resource. ;
Appears in Collections:General Science

Files in This Item:
File SizeFormat 
9783319706887.pdf8.07 MBAdobe PDF