Computational Intelligence Applications in Business Intelligence and Big Data Analytics. (Record no. 71515)

000 -LEADER
fixed length control field 03965cam a2200529Ma 4500
001 - CONTROL NUMBER
control field 9781351720250
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711212532.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 170811s2017 enka o 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1351720252
-- (ebk)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781351720250
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781498761024
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 149876102X
082 04 - CLASSIFICATION NUMBER
Call Number 658.4
100 1# - AUTHOR NAME
Author Sugumaran, Vijayan.
245 10 - TITLE STATEMENT
Title Computational Intelligence Applications in Business Intelligence and Big Data Analytics.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication London :
Publisher CRC Press,
Year of publication 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (348 pages) :
520 2# - SUMMARY, ETC.
Summary, etc "There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book."--Provided by publisher.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- Editors -- Contributors -- PART I: INTRODUCTION -- 1 Computational Intelligence Paradigms in Business Intelligence and Analytics -- PART II: COMPUTATIONAL INTELLIGENCE IN BUSINESS INTELLIGENCE AND ANALYTICS -- 2 Conditional Value at Risk-Based Portfolio Optimization Using Metaheuristic Approaches -- 3 Big Data Analysis and Application for Video Surveillance Systems -- 4 Trends in Mining Biological Big Data -- 5 Computational Challenges in Group Membership Prediction of Highly Imbalanced Big Data Sets -- PART III: DATA ANALYTICS AND PREDICTION MODELS -- 6 A New Paradigm in Fraud Detection Modeling Using Predictive Models, Fuzzy Expert Systems, Social Network Analysis, and Unstructured Data -- 7 Speedy Data Analytics through Automatic Balancing of Big Data in MongoDB Sharded Clusters -- 8 Smart Metering as a Service Using Hadoop (SMAASH) -- 9 Service-Oriented Architecture for Big Data and Business Intelligence Analytics in the Cloud -- PART IV: APPLICATIONS OF COMPUTATIONAL INTELLIGENCE -- 10 Rough Set and Neighborhood Systems in Big Data Analysis -- 11 An Investigation of Fuzzy Techniques in Clustering of Big Data -- 12 A Survey on Learning Models with Respect to Human Behavior Analysis for Large-Scale Surveillance Videos -- 13 Mining Unstructured Big Data for Competitive Intelligence and Business Intelligence -- Index.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Management.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.taylorfrancis.com/books/9781351720250
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.taylorfrancis.com/books/9781315180748
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
588 ## -
-- OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information technology
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Big data.
938 ## -
-- Taylor & Francis
-- TAFR
-- 9781315180748

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