Data Science and Big Data An Environment of Computational Intelligence

Data Science and Big Data  An Environment of Computational Intelligence
Author: Witold Pedrycz,Shyi-Ming Chen
Publsiher: Springer
Total Pages: 303
Release: 2017-03-21
ISBN: 3319534742
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Data Science and Big Data An Environment of Computational Intelligence Book Excerpt:

This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today’s knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.

Data Science and Big Data Computing

Data Science and Big Data Computing
Author: Zaigham Mahmood
Publsiher: Springer
Total Pages: 319
Release: 2016-07-05
ISBN: 3319318616
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Data Science and Big Data Computing Book Excerpt:

This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.

Big Data Science and Analytics for Smart Sustainable Urbanism

Big Data Science and Analytics for Smart Sustainable Urbanism
Author: Simon Elias Bibri
Publsiher: Springer
Total Pages: 337
Release: 2019-05-30
ISBN: 3030173127
Category: Political Science
Language: EN, FR, DE, ES & NL

Big Data Science and Analytics for Smart Sustainable Urbanism Book Excerpt:

We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.

Distributed Computing in Big Data Analytics

Distributed Computing in Big Data Analytics
Author: Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka
Publsiher: Springer
Total Pages: 162
Release: 2017-08-29
ISBN: 3319598341
Category: Computers
Language: EN, FR, DE, ES & NL

Distributed Computing in Big Data Analytics Book Excerpt:

Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.

Emerging Technologies in Computer Engineering Microservices in Big Data Analytics

Emerging Technologies in Computer Engineering  Microservices in Big Data Analytics
Author: Arun K. Somani,Seeram Ramakrishna,Anil Chaudhary,Chothmal Choudhary,Basant Agarwal
Publsiher: Springer
Total Pages: 364
Release: 2019-05-17
ISBN: 9811383006
Category: Computers
Language: EN, FR, DE, ES & NL

Emerging Technologies in Computer Engineering Microservices in Big Data Analytics Book Excerpt:

This book constitutes the refereed proceedings of the Second International Conference on Emerging Technologies in Computer Engineering: Microservices in Big Data Analytics, ICETCE 2019, held in Jaipur, India, in February 2019. The 28 revised full papers along with 1 short paper presented were carefully reviewed and selected from 253 submissions. ICETCE conference aims to showcase advanced technologies, techniques, innovations and equipments in computer engineering. It provides a platform for researchers, scholars, experts, technicians, government officials and industry personnel from all over the world to discuss and share their valuable ideas and experiences.

Cloud Computing Enabled Big Data Analytics in Wireless Ad hoc Networks

Cloud Computing Enabled Big Data Analytics in Wireless Ad hoc Networks
Author: Sanjoy Das,Ram Shringar Rao,Indrani Das,Vishal Jain,Nanhay Singh
Publsiher: CRC Press
Total Pages: 290
Release: 2022-03-22
ISBN: 1000539490
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Cloud Computing Enabled Big Data Analytics in Wireless Ad hoc Networks Book Excerpt:

This book discusses intelligent computing through Internet of Things (IoT) and Big Data in vehicular environments in a single volume. It covers important topics, such as topology-based routing protocols, heterogeneous wireless networks, security risks, software-defined vehicular ad-hoc networks, vehicular delay tolerant networks, and energy harvesting for WSNs using rectenna. Features Covers applications of IoT in Vehicular Ad-hoc Network (VANETs) Discusses use of machine learning and other computing techniques for enhancing performance of networks Explains game theory-based vertical handoffs in heterogeneous wireless networks Examines monitoring and surveillance of vehicles through the vehicular sensor network Investigates theoretical approaches on software-defined VANET The book is aimed at graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science, and engineering.

Big Data Analytics and Computing for Digital Forensic Investigations

Big Data Analytics and Computing for Digital Forensic Investigations
Author: Suneeta Satpathy,Sachi Nandan Mohanty
Publsiher: CRC Press
Total Pages: 214
Release: 2020-03-17
ISBN: 100004503X
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics and Computing for Digital Forensic Investigations Book Excerpt:

Digital forensics has recently gained a notable development and become the most demanding area in today’s information security requirement. This book investigates the areas of digital forensics, digital investigation and data analysis procedures as they apply to computer fraud and cybercrime, with the main objective of describing a variety of digital crimes and retrieving potential digital evidence. Big Data Analytics and Computing for Digital Forensic Investigations gives a contemporary view on the problems of information security. It presents the idea that protective mechanisms and software must be integrated along with forensic capabilities into existing forensic software using big data computing tools and techniques. Features Describes trends of digital forensics served for big data and the challenges of evidence acquisition Enables digital forensic investigators and law enforcement agencies to enhance their digital investigation capabilities with the application of data science analytics, algorithms and fusion technique This book is focused on helping professionals as well as researchers to get ready with next-generation security systems to mount the rising challenges of computer fraud and cybercrimes as well as with digital forensic investigations. Dr Suneeta Satpathy has more than ten years of teaching experience in different subjects of the Computer Science and Engineering discipline. She is currently working as an associate professor in the Department of Computer Science and Engineering, College of Bhubaneswar, affiliated with Biju Patnaik University and Technology, Odisha. Her research interests include computer forensics, cybersecurity, data fusion, data mining, big data analysis and decision mining. Dr Sachi Nandan Mohanty is an associate professor in the Department of Computer Science and Engineering at ICFAI Tech, ICFAI Foundation for Higher Education, Hyderabad, India. His research interests include data mining, big data analysis, cognitive science, fuzzy decision-making, brain–computer interface, cognition and computational intelligence.

Big Data Cloud Computing Data Science Engineering

Big Data  Cloud Computing  Data Science   Engineering
Author: Roger Lee
Publsiher: Springer
Total Pages: 189
Release: 2018-08-13
ISBN: 3319968033
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Big Data Cloud Computing Data Science Engineering Book Excerpt:

This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.

Big Data Analytics for Sustainable Computing

Big Data Analytics for Sustainable Computing
Author: Haldorai, Anandakumar,Ramu, Arulmurugan
Publsiher: IGI Global
Total Pages: 263
Release: 2019-09-20
ISBN: 1522597522
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics for Sustainable Computing Book Excerpt:

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.

HCI Challenges and Privacy Preservation in Big Data Security

HCI Challenges and Privacy Preservation in Big Data Security
Author: Lopez, Daphne,Durai, M.A. Saleem
Publsiher: IGI Global
Total Pages: 275
Release: 2017-08-10
ISBN: 1522528644
Category: Computers
Language: EN, FR, DE, ES & NL

HCI Challenges and Privacy Preservation in Big Data Security Book Excerpt:

Privacy protection within large databases can be a challenge. By examining the current problems and challenges this domain is facing, more efficient strategies can be established to safeguard personal information against invasive pressures. HCI Challenges and Privacy Preservation in Big Data Security is an informative scholarly publication that discusses how human-computer interaction impacts privacy and security in almost all sectors of modern life. Featuring relevant topics such as large scale security data, threat detection, big data encryption, and identity management, this reference source is ideal for academicians, researchers, advanced-level students, and engineers that are interested in staying current on the advancements and drawbacks of human-computer interaction within the world of big data.

Big Data Analytics for Cloud IoT and Cognitive Computing

Big Data Analytics for Cloud  IoT and Cognitive Computing
Author: Kai Hwang,Min Chen
Publsiher: John Wiley & Sons
Total Pages: 432
Release: 2017-08-14
ISBN: 1119247020
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics for Cloud IoT and Cognitive Computing Book Excerpt:

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

Data Science and Big Data Analytics

Data Science and Big Data Analytics
Author: Durgesh Kumar Mishra,Xin-She Yang,Aynur Unal
Publsiher: Springer
Total Pages: 406
Release: 2018-08-01
ISBN: 9811076413
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Data Science and Big Data Analytics Book Excerpt:

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.

High Performance Big Data Analytics

High Performance Big Data Analytics
Author: Pethuru Raj,Anupama Raman,Dhivya Nagaraj,Siddhartha Duggirala
Publsiher: Springer
Total Pages: 428
Release: 2015-10-16
ISBN: 331920744X
Category: Computers
Language: EN, FR, DE, ES & NL

High Performance Big Data Analytics Book Excerpt:

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.

Big Data Analytics

Big Data Analytics
Author: V. B. Aggarwal,Vasudha Bhatnagar,Durgesh Kumar Mishra
Publsiher: Springer
Total Pages: 766
Release: 2017-10-03
ISBN: 9811066205
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics Book Excerpt:

This volume comprises the select proceedings of the annual convention of the Computer Society of India. Divided into 10 topical volumes, the proceedings present papers on state-of-the-art research, surveys, and succinct reviews. The volumes cover diverse topics ranging from communications networks to big data analytics, and from system architecture to cyber security. This volume focuses on Big Data Analytics. The contents of this book will be useful to researchers and students alike.

Innovations in Computer Science and Engineering

Innovations in Computer Science and Engineering
Author: H. S. Saini,Rishi Sayal,A. Govardhan,Rajkumar Buyya
Publsiher: Springer Nature
Total Pages: 712
Release: 2022-03-25
ISBN: 9811689873
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Innovations in Computer Science and Engineering Book Excerpt:

This book features a collection of high-quality, peer-reviewed research papers presented at the 9th International Conference on Innovations in Computer Science & Engineering (ICICSE 2021), held at Guru Nanak Institutions, Hyderabad, India, on September 3–4, 2021. It covers the latest research in data science and analytics, cloud computing, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks and IoT applications, artificial intelligence, expert systems, natural language processing, image processing, computer vision, and artificial neural networks.

Smart Metro Station Systems

Smart Metro Station Systems
Author: Hui Liu,Chao Chen,Yanfei Li,Zhu Duan,Ye Li
Publsiher: Elsevier
Total Pages: 316
Release: 2022-01-17
ISBN: 0323907121
Category: Transportation
Language: EN, FR, DE, ES & NL

Smart Metro Station Systems Book Excerpt:

Smart Metro Station Systems: Data Science and Engineering introduces key technologies in data science and engineering for smart metro station systems. The book consists of three main parts, focusing on the environment, people and energy. Each chapter includes practical applications, along with information on metro traffic flow monitoring and passenger guidance, methods for behavior analysis and trajectory projection, clustering and anomaly detection in crowd hotspots, monitoring and prediction for station humidity, monitoring and spatial prediction for air pollutants, time series feature extraction and analysis of metro load, characteristic and correlation analysis of metro load, and prediction and intelligent ventilation control. This volume offers a key reference on the emerging area of smart metro stations and will be useful to those working on smart railways, data science, engineering, artificial intelligence and aligned fields. Presents relevant core technologies of data science and engineering in smart metro station systems Describes systems based on holographic perception, terminal platform control and highly-autonomous operation Gives a large number of practical case studies and experimental designs Introduces state-of-the-art machine learning and data mining methods for smart metro station systems Offers a comprehensive, up-to-date research solution for the emerging area of smart metro stations

Applications of Big Data in Large and Small Scale Systems

Applications of Big Data in Large  and Small Scale Systems
Author: Goundar, Sam,Rayani, Praveen Kumar
Publsiher: IGI Global
Total Pages: 377
Release: 2021-01-15
ISBN: 1799866750
Category: Computers
Language: EN, FR, DE, ES & NL

Applications of Big Data in Large and Small Scale Systems Book Excerpt:

With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Intelligent Computing and Innovation on Data Science

Intelligent Computing and Innovation on Data Science
Author: Sheng-Lung Peng,Sun-Yuan Hsieh,Suseendran Gopalakrishnan,Balaganesh Duraisamy
Publsiher: Springer Nature
Total Pages: 590
Release: 2021-09-27
ISBN: 9811631530
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Intelligent Computing and Innovation on Data Science Book Excerpt:

This book gathers high-quality papers presented at 2nd International Conference on Technology Innovation and Data Sciences (ICTIDS 2021), organized by Lincoln University, Malaysia from 19 – 20 February 2021. It covers wide range of recent technologies like artificial intelligence and machine learning, big data and data sciences, Internet of Things (IoT), and IoT-based digital ecosystem. The book brings together works from researchers, scientists, engineers, scholars and students in the areas of engineering and technology, and provides an opportunity for the dissemination of original research results, new ideas, research and development, practical experiments, which concentrate on both theory and practices, for the benefit of common man.

14th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2019

14th International Conference on Soft Computing Models in Industrial and Environmental Applications  SOCO 2019
Author: Francisco Martínez Álvarez,Alicia Troncoso Lora,José António Sáez Muñoz,Héctor Quintián,Emilio Corchado
Publsiher: Springer
Total Pages: 609
Release: 2019-04-30
ISBN: 3030200558
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

14th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2019 Book Excerpt:

This book includes 57 papers presented at the SOCO 2019 conference held in the historic city of Seville (Spain), in May 2019. Soft computing represents a set of computational techniques in machine learning, computer science and various engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. The selection of papers was extremely rigorous in order to maintain the high quality of the conference, which featured a number of special sessions, including sessions on: Soft Computing Methods in Manufacturing and Management Systems; Soft Computing Applications in the Field of Industrial and Environmental Enterprises; Optimization, Modeling and Control by Soft Computing Techniques; and Soft Computing in Aerospace, Mechanical and Civil Engineering: New methods and Industrial Applications.

Cognitive Computing and Big Data Analytics

Cognitive Computing and Big Data Analytics
Author: Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Publsiher: John Wiley & Sons
Total Pages: 288
Release: 2015-04-08
ISBN: 1118896785
Category: Computers
Language: EN, FR, DE, ES & NL

Cognitive Computing and Big Data Analytics Book Excerpt:

A comprehensive guide to learning technologies that unlock thevalue in big data Cognitive Computing provides detailed guidance towardbuilding a new class of systems that learn from experience andderive insights to unlock the value of big data. This book helpstechnologists understand cognitive computing's underlyingtechnologies, from knowledge representation techniques and naturallanguage processing algorithms to dynamic learning approaches basedon accumulated evidence, rather than reprogramming. Detailed caseexamples from the financial, healthcare, and manufacturing walkreaders step-by-step through the design and testing of cognitivesystems, and expert perspectives from organizations such asCleveland Clinic, Memorial Sloan-Kettering, as well as commercialvendors that are creating solutions. These organizations provideinsight into the real-world implementation of cognitive computingsystems. The IBM Watson cognitive computing platform is describedin a detailed chapter because of its significance in helping todefine this emerging market. In addition, the book includesimplementations of emerging projects from Qualcomm, Hitachi, Googleand Amazon. Today's cognitive computing solutions build on establishedconcepts from artificial intelligence, natural language processing,ontologies, and leverage advances in big data management andanalytics. They foreshadow an intelligent infrastructure thatenables a new generation of customer and context-aware smartapplications in all industries. Cognitive Computing is a comprehensive guide to thesubject, providing both the theoretical and practical guidancetechnologists need. Discover how cognitive computing evolved from promise toreality Learn the elements that make up a cognitive computingsystem Understand the groundbreaking hardware and softwaretechnologies behind cognitive computing Learn to evaluate your own application portfolio to find thebest candidates for pilot projects Leverage cognitive computing capabilities to transform theorganization Cognitive systems are rightly being hailed as the new era ofcomputing. Learn how these technologies enable emerging firms tocompete with entrenched giants, and forward-thinking establishedfirms to disrupt their industries. Professionals who currently workwith big data and analytics will see how cognitive computing buildson their foundation, and creates new opportunities. CognitiveComputing provides complete guidance to this new level ofhuman-machine interaction.