Smart Data

State-of-the-Art Perspectives in Computing and Applications

Häftad, Engelska, 2020

Av Kuan-Ching Li, Laurence T. Yang, Qingchen Zhang, Beniamino Di Martino, Taiwan) Li, Kuan-Ching (Providence University, Canada) Yang, Laurence T. (St. Francis Xavier University, Italy) Di Martino, Beniamino (Universita della Campania

839 kr

Beställningsvara. Skickas inom 10-15 vardagar

Fri frakt för medlemmar vid köp för minst 249 kr.

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more.Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers

Produktinformation

Utgivningsdatum2020-09-30
Mått178 x 254 x undefined mm
Vikt790 g
FormatHäftad
SpråkEngelska
SerieChapman & Hall/CRC Big Data Series
Antal sidor410
FörlagTaylor & Francis Ltd
ISBN9780367656478

Tillhör följande kategorier

Databaser inom Data och it

Foreword, ixAcknowledgement, xiEditors, xiiiList of Contributors, xvCHAPTER 1 ■ Extreme Heterogeneity in Deep Learning Architectures 1JEFF ANDERSON, ARMIN MEHRABIAN, JIAXIN PENG, AND TAREK EL-GHAZAWICHAPTER 2 ■ GPU PaaS Computation Model in Aneka CloudComputing Environments 19SHASHIKANT ILAGER, RAJEEV WANKAR, RAGHAVENDRA KUNE, AND RAJKUMAR BUYYACHAPTER 3 ■ Toward Complex Search for Encrypted Mobile CloudData via Index Blind Storage 41YUPENG HU, LINJUN WU, WENJIA LI, KEQIN LI, YONGHE LIU, AND ZHENG QINCHAPTER 4 ■ Encrypted Big Data Deduplication in Cloud Storage 63ZHENG YAN, XUEQIN LIANG, WENXIU DING, XIXUN YU, MINGJUN WANG, ANDROBERT H. DENGCHAPTER 5 ■ The Role of NonSQL Databases in Big Data 93ANTONIO SARASA CABEZUELOCHAPTER 6 ■ Prescriptive and Predictive Analytics Techniques forEnabling Cybersecurity 113NITIN SUKHIJA, SONNY SEVIN, ELIZABETH BAUTISTA, AND DAVID DAMPIERCHAPTER 7 ■ Multivariate Projection Techniques to ReduceDimensionality in Large Datasets 133I. BARRANCO CHAMORRO, S. MUÑOZ-ARMAYONES, A. ROMERO-LOSADA,AND F. ROMERO-CAMPEROCHAPTER 8 ■ Geo-Distributed Big Data Analytics Systems: AnOnline Learning Approach for Dynamic Deployment 161YIXIN BAO AND CHUAN WUCHAPTER 9 ■ The Role of Smart Data in Inference of Human Behaviorand Interaction 191RUTE C. SOFIA, LILIANA CARVALHO, AND FRANCISCO M. PEREIRACHAPTER 10 ■ Compression of Wearable Body Sensor Network Data 215ROBINSON RAJU, MELODY MOH, AND TENG-SHENG MOHCHAPTER 11 ■ Population-Specific and Personalized (PSP) Models ofHuman Behavior for Leveraging Smart andConnected Data 243THEODORA CHASPARI, ADELA C. TIMMONS, AND GAYLA MARGOLINCHAPTER 12 ■ Detecting Singular Data for Better Analysis ofEmotional Tweets 259KIICHI TAGO, KENICHI ITO, AND QUN JINCHAPTER 13 ■ Smart Data Infrastructure for Respiratory HealthProtection of Citizens against PM2.5 in Urban Areas 273DANIEL DUNEA, STEFANIA IORDACHE, ALIN POHOATA, AND EMIL LUNGUCHAPTER 14 ■ Fog-Assisted Cloud Platforms for Big Data Analytics inCyber Physical Systems: A Smart Grid Case Study 289MD. MUZAKKIR HUSSAIN, MOHAMMAD SAAD ALAM, AND M.M. SUFYAN BEGCHAPTER 15 ■ When Big Data and Data Science Prefigured AmbientIntelligence 319CHRISTOPHE THOVEXCHAPTER 16 ■ Ethical Issues and Considerations of Big Data 343EDWARD T. CHENCHAPTER 17 ■ Data Protection by Design in Smart Data Environments 359PAOLO BALBONIINDEX, 391

"The book is a great resource for all those interested in learning about the interplay between "smart data" and a number of research themes: algorithms, applications, ethical issues, security and data privacy, among many other topics. The book will be very useful for researchers, practitioners, and graduate students; a welcome addition to the Smart Data literature. The book is a milestone in this fast-moving field." — Professor Albert Y. Zomaya, Sydney University, Australia "This book provides a precious set of high-level research contributions for learning how to extract Smart Data from Big Data. Novel intelligent techniques, models, algorithms and applications are presented and discussed. Young researchers and professionals will benefit from the book contents to learn new topics and investigate new research issues. From infrastructure and algorithms to applications and ethics, Smart Data are illustrated and put in practice." — Professor Domenico Talia, Università della Calabria, Italy