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001 on1345273842
003 OCoLC
005 20230113054233.0
006 m o d
007 cr |n|||||||||
008 220922t20222022enka o 0|1 0 eng d
020 1839534893|q(PDF)
020 9781839534898|q(electronic book)
020 |z1839534885|q(hardback)
020 |z9781839534881|q(hardback)
035 (OCoLC)1345273842
040 YDX|beng|erda|cYDX|dUAB|dSTF|dUIU|dOCLCF|dN$T|dUKAHL
049 RIDW
050 4 QA166
082 04 511.5|223
090 QA166
245 00 Demystifying graph data science:|bgraph algorithms,
analytics methods, platforms, databases, and use cases /
|cedited by Pethuru Raj, Abhishek Kumar, Vicente García
Díaz and Nachamai Muthurama.
264 1 London :|bThe Institution of Engineering and Technology,
|c2022.
264 4 |c©2022
300 1 online resource (xxi, 391 pages) :|billustrations.
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
347 text file|2rdaft
490 1 IET computing series ;|v48
500 Includes index.
520 With the growing maturity and stability of digitization
and edge technologies, vast numbers of digital entities,
connected devices, and microservices interact purposefully
to create huge sets of poly-structured digital data.
Corporations are continuously seeking fresh ways to use
their data to drive business innovations and disruptions
to bring in real digital transformation. Data science (DS)
is proving to be the one-stop solution for simplifying the
process of knowledge discovery and dissemination out of
massive amounts of multi-structured data. Supported by
query languages, databases, algorithms, platforms,
analytics methods and machine and deep learning (ML and
DL) algorithms, graphs are now emerging as a new data
structure for optimally representing a variety of data and
their intimate relationships. Compared to traditional
analytics methods, the connectedness of data points in
graph analytics facilitates the identification of clusters
of related data points based on levels of influence,
association, interaction frequency and probability. Graph
analytics is being empowered through a host of path-
breaking analytics techniques to explore and pinpoint
beneficial relationships between different entities such
as organizations, people and transactions. This edited
book aims to explain the various aspects and importance of
graph data science. The authors from both academia and
industry cover algorithms, analytics methods, platforms
and databases that are intrinsically capable of creating
business value by intelligently leveraging connected data.
This book will be a valuable reference for ICTs industry
and academic researchers, scientists and engineers, and
lecturers and advanced students in the fields of data
analytics, data science, cloud/fog/edge architecture,
internet of things, artificial intelligence/machine and
deep learning, and related fields of applications. It will
also be of interest to analytics professionals in industry
and IT operations teams.
588 0 Online resource; title from title page (viewed September
22, 2022).
590 eBooks on EBSCOhost|bEBSCO eBook Subscription Academic
Collection - North America
650 0 Graph theory|0https://id.loc.gov/authorities/subjects/
sh85056471|xComputer programs.|0https://id.loc.gov/
authorities/subjects/sh99005296
650 7 Graph theory|xComputer programs.|2fast|0https://
id.worldcat.org/fast/946585
650 7 Graph theory.|2fast|0https://id.worldcat.org/fast/946584
700 1 Raj, Pethuru,|0https://id.loc.gov/authorities/names/
n2012071848|eeditor.
700 1 Kumar, Abhishek,|0https://id.loc.gov/authorities/names/
no2013101885|eeditor.
700 1 García Díaz, Vicente,|eeditor.
700 1 Muthurama, Nachamai,|eeditor.
776 08 |iPrint version:|z1839534885|z9781839534881
|w(OCoLC)1322045952
830 0 IET computing series ;|v48.
856 40 |uhttps://rider.idm.oclc.org/login?url=https://
search.ebscohost.com/login.aspx?direct=true&scope=site&
db=nlebk&AN=3387634|zOnline ebook via EBSCO. Access
restricted to current Rider University students, faculty,
and staff.
856 42 |3Instructions for reading/downloading the EBSCO version
of this ebook|uhttp://guides.rider.edu/ebooks/ebsco
901 MARCIVE 20231220
948 |d20230203|cEBSCO|tEBSCOebooksacademic NEW 6073 Quarterly
|lridw
994 92|bRID
