Название: Handbook of Big Data Analytics : Applications in ICT, Security and Business Analytics, Volume 2 Автор: Vadlamani Ravi, Aswani Kumar Cherukuri Издательство: The Institution of Engineering and Technology Год: 2021 Страниц: 419 Язык: английский Формат: pdf (true) Размер: 14.2 MB
Big Data analytics is the complex process of examining big data to uncover information such as correlations, hidden patterns, trends and user and customer preferences, to allow organizations and businesses to make more informed decisions.
The second volume is dedicated to a wide range of applications in secure data storage, privacy-preserving, Software Defined Networks (SDN), Internet of Things (IoTs), behaviour analytics, traffic predictions, gender based classification on e-commerce data, recommender systems, Big Data regression with Apache Spark, visual sentiment analysis, wavelet Neural Network via GPU, stock market movement predictions, and financial reporting.
The two-volume work is aimed at providing a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics.
Contents:
Preface Introduction 1 Big data analytics for security intelligence 2 Zero attraction data selective adaptive filtering algorithm for Big Data applications 3 Secure routing in software defined networking and Internet of Things for Big Data 3.8 The arrival of SDN into big data and IoT 3.9 Architecture of SDN 3.10 Routing in SDN 3.11 Attacks on SDN and existing solutions 4 Efficient ciphertext-policy attribute-based signcryption for secure Big Data storage in cloud 5 Privacy-preserving techniques in Big Data 6 Big Data and behaviour analytics 6.5 Existing algorithms, tools available for data analytics and behaviour analytics 6.5.1 Apache Hadoop 6.5.2 Cloudera 6.5.3 Cassandra 6.5.4 Konstanz Information Miner 6.5.5 Data wrapper 6.5.6 MongoDB 6.5.7 HPCC 7 Analyzing events for traffic prediction on IoT data streams in a smart city scenario 8 Gender-based classification on e-commerce Big Data 9 On recommender systems with Big Data 10 Analytics in e-commerce at scale 11 Big Data regression via parallelized radial basis function neural network in Apache Spark 12 Visual sentiment analysis of bank customer complaints using parallel self-organizing maps 13 Wavelet neural network for Big Data analytics in banking via GPU 14 Stock market movement prediction using evolving spiking neural networks 15 Parallel hierarchical clustering of big text corpora 16 Contract-driven financial reporting: building automated analytics pipelines with algorithmic contracts, Big Data and Distributed Ledger technology Overall conclusions Index 373
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