Central Library

Normal view MARC view ISBD view

Computational Intelligence Applications in Business Intelligence and Big Data Analytics.

By: Sugumaran, Vijayan.
Material type: materialTypeLabelBookPublisher: London : CRC Press, 2017Description: 1 online resource (348 pages) : illustrations.Content type: text Media type: computer Carrier type: online resourceISBN: 1351720252; 9781351720250; 9781498761024; 149876102X.Subject(s): Information technology -- Management | Computational intelligence | Big dataDDC classification: 658.4 Online resources: Taylor & Francis Distributed by publisher. Purchase or institutional license may be required for access. | Taylor & Francis Click here to view. | OCLC metadata license agreement
Contents:
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.
Scope and content: "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.
    average rating: 0.0 (0 votes)
No physical items for this record

"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.

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.

OCLC-licensed vendor bibliographic record.

There are no comments for this item.

Log in to your account to post a comment.