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Big Data Analytics: Systems, Algorithms, Applications, C.S.R. Prabhu; Aneesh Sreevallabh Chivukula; Adity


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Автор: C.S.R. Prabhu; Aneesh Sreevallabh Chivukula; Adity
Название:  Big Data Analytics: Systems, Algorithms, Applications
ISBN: 9789811500930
Издательство: Springer
Классификация:


ISBN-10: 9811500932
Обложка/Формат: Hardcover
Страницы: 412
Вес: 1.01 кг.
Дата издания: 2019
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 108 illustrations, color; 66 illustrations, black and white; xxvi, 412 p. 174 illus., 108 illus. in color.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:
This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy.
With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered.
In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition.
Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Дополнительное описание: Big Data.- Intelligent Systems.- Analytics Models for Data Science.- Big Data Tools – Hadoop Eco System.- Predictive Modeling for Unstructured Data.- Machine Learning Algorithms for Big Data.- Social Semantic Web Mining and Big Data Analytics.- Internet



Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner

Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel
Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
ISBN: 1118729277 ISBN-13(EAN): 9781118729274
Издательство: Wiley
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Цена: 17741.00 р.
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Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.

Advancing Cloud Database Systems and Capacity Planning with Dynamic Applications

Автор: Kamila Narendra Kumar
Название: Advancing Cloud Database Systems and Capacity Planning with Dynamic Applications
ISBN: 1522520139 ISBN-13(EAN): 9781522520139
Издательство: Mare Nostrum (Eurospan)
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Цена: 30631.00 р.
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Описание: Continuous improvements in data analysis and cloud computing have allowed more opportunities to develop systems with user-focused designs. This not only leads to higher success in day-to-day usage, but it increases the overall probability of technology adoption.Advancing Cloud Database Systems and Capacity Planning with Dynamic Applications is a key resource on the latest innovations in cloud database systems and their impact on the daily lives of people in modern society. Highlighting multidisciplinary studies on information storage and retrieval, big data architectures, and artificial intelligence, this publication is an ideal reference source for academicians, researchers, scientists, advanced level students, technology developers and IT officials.

Data Analytics Applications in Gaming and Entertainment

Автор: Gunter Wallner
Название: Data Analytics Applications in Gaming and Entertainment
ISBN: 1138104434 ISBN-13(EAN): 9781138104433
Издательство: Taylor&Francis
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Цена: 16078.00 р.
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Описание: Over the last decade big data and data mining has received growing interest and importance in game production to process and draw actionable insights from large volumes of player-related data in order to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation.

Cloud Infrastructures For Big Data Analytics

Автор: Raj & Chandra Deka
Название: Cloud Infrastructures For Big Data Analytics
ISBN: 1466658649 ISBN-13(EAN): 9781466658646
Издательство: Mare Nostrum (Eurospan)
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Цена: 50312.00 р.
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Описание: Clouds are being positioned as the next-generation consolidated, centralised, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional, applications and services.Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organisations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.

Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining

Автор: Emmanouil Amolochitis
Название: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining
ISBN: 8793609647 ISBN-13(EAN): 9788793609648
Издательство: Taylor&Francis
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Цена: 11789.00 р.
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Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.

Agile Data Science: Building Full-Stack Data Analytics Applications with Spark

Название: Agile Data Science: Building Full-Stack Data Analytics Applications with Spark
ISBN: 1491960116 ISBN-13(EAN): 9781491960110
Издательство: Wiley
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Цена: 7602.00 р.
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Описание: With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.

Cognitive Social Mining Applications in Data Analytics and Forensics

Автор: Anandakumar Haldorai, Arulmurugan Ramu
Название: Cognitive Social Mining Applications in Data Analytics and Forensics
ISBN: 1522575227 ISBN-13(EAN): 9781522575221
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data.Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.

Quantitative Analysis for System Applications: Data Science and Analytics Tools and Techniques

Автор: Daniel A McGrath
Название: Quantitative Analysis for System Applications: Data Science and Analytics Tools and Techniques
ISBN: 1634624238 ISBN-13(EAN): 9781634624237
Издательство: Gazelle Book Services
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Цена: 10723.00 р.
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Описание:

As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.

Here are just a dozen of the many questions answered within these pages:

  1. What does quantitative analysis of a system really mean?
  2. What is a system?
  3. What are big data and analystics?
  4. How do you know your numbers are good?
  5. What will the future data science environment look like?
  6. How do you determine data provenance?
  7. How do you gather and process information, and then organize, store, and synthesize it?
  8. How does an organization implement data analytics?
  9. Do you really need to think like a Chief Information Officer?
  10. What is the best way to protect data?
  11. What makes a good dashboard?
  12. What is the relationship between eating ice cream and getting attacked by a shark?

The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).

Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.

Decision Support Systems V – Big Data Analytics for Decision Making

Автор: Boris Deliba?i?; Jorge E. Hern?ndez; Jason Papatha
Название: Decision Support Systems V – Big Data Analytics for Decision Making
ISBN: 3319185322 ISBN-13(EAN): 9783319185323
Издательство: Springer
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Цена: 5590.00 р.
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Описание: 'Big Data' Decision Making Use Cases.- The Roles of Big Data in the Decision-Support Process: An Empirical Investigation.- Cloud Enabled Big Data Business Platform for Logistics Services: A Research and Development Agenda.- Making Sense of Governmental Activities Over Social Media: A Data-Driven Approach.- Data-Mining and Expert Models for Predicting Injury Risk in Ski Resorts.- The Effects of Performance Ratios in Predicting Corporate Bankruptcy: The Italian Case.- A Tangible Collaborative Decision Support System for Various Variants of the Vehicle Routing Problem.- Decision Support Model for Participatory Management of Water Resource.- Modeling Interactions Among Criteria in MCDM Methods: A Review.

Data Analytics for Businesses 2019: Master Data Science with Optimised Marketing Strategies using Data Mining Algorithms (Artificial Intelligence, Mac

Автор: Adams Riley
Название: Data Analytics for Businesses 2019: Master Data Science with Optimised Marketing Strategies using Data Mining Algorithms (Artificial Intelligence, Mac
ISBN: 1999177053 ISBN-13(EAN): 9781999177058
Издательство: Неизвестно
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Цена: 3677.00 р.
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Описание:

Are you looking for new ways to grow your business, with resources you already have? Do you want to know how the big players like Netflix, Amazon, or Shopify use data analytics to MULTIPLY their growth? Keep listening to learn how to use data analytics to maximise YOUR business.

Yes, you have customers that love your product. However, you're having trouble finding new customers and captivating their attention. You realized you're also losing customers, and you have no clue what you can do to prevent this from happening. How do I stand out in a crowd of businesses? How do I target my perfect client and make them choose ME? If this sounds like you, Data Analytics for Businesses if the guide you need.

This book will walk you through the fundamental principles of data science and how to apply the "data analytic mindset" when approaching your business. You will learn how to extract valuable insights from data sources you ALREADY HAVE, and make informed business decisions to help you achieve your goals.

With real-world examples of how to apply data analytics to your business, this book does what others fail to do. Break the process down step by step, so you can optimize unique parts of your business; such as improving customer loyalty or reducing churn. This guide also helps you understand the many data-mining techniques in use today.

Discover the value of applied data science for business decision-making. You'll learn how to think data-analytically, and make connections between data sources to unveil insights you've never imagined. In this book you will learn:

✔︎ Why every company should be leveraging Data Analytics
✔︎ The difference between Big Data, Data Science and Data Analytics.
✔︎ How to achieve your goals by applying data-analytical thinking to your business
✔︎ The recommended data mining techniques for each of your business goals.
✔︎ The most important thing to remember when extracting knowledge from your data.
✔︎ How to use data analytics to improve brand loyalty and customer experience.
✔︎ How to hire the best data scientist, and more.

If you are overwhelmed by this whole new topic of data analytics, don't be. This guide is designed for beginners, with all the guidance you need to understand the fundamentals of harnessing data analytics for your business. So even if you have never heard about data analytics until today, I promise we will walk through this step- by-step.

By the end of this, you'll be able to think analytically and make informed business decisions. This book illustrates how EASY it is to find success by just applying a few principles.

So stop reading this description, and start reading Data Analytics for Businesses instead. Scroll up, and CLICK BUY now

Big data applications in the telecommunications industry /

Автор: Mantian Hu and Ye Ouyang
Название: Big data applications in the telecommunications industry /
ISBN: 1522517502 ISBN-13(EAN): 9781522517504
Издательство: Mare Nostrum (Eurospan)
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Цена: 21206.00 р.
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Описание: The growing presence of smart phones and smart devices has caused significant changes to wireless networks. With the ubiquity of these technologies, there is now increasingly more available data for mobile operators to utilize.Big Data Applications in the Telecommunications Industry is a comprehensive reference source for the latest scholarly material on the use of data analytics to study wireless networks and examines how these techniques can increase reliability and profitability, as well as network performance and connectivity. Featuring extensive coverage on relevant topics, such as accessibility, traffic data, and customer satisfaction, this publication is ideally designed for engineers, students, professionals, academics, and researchers seeking innovative perspectives on data science and wireless network communications.Topics CoveredThe many academic areas covered in this publication include, but are not limited to:Anomaly DetectionCo-Occurrence Data ModelingConsumer FeedbackCustomer Satisfaction and RetentionNetwork AccessibilitySocial NetworksTraffic Data

Advanced applications of supercritical fluids in energy systems /

Автор: CHEN & IWAMOTO
Название: Advanced applications of supercritical fluids in energy systems /
ISBN: 1522520473 ISBN-13(EAN): 9781522520474
Издательство: Turpin
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Цена: 34742.00 р.
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Описание: Supercritical fluids have been utilized for numerous scientific advancements and industrial innovations. As the concern for environmental sustainability grows, these fluids have been increasingly used for energy efficiency purposes.Advanced Applications of Supercritical Fluids in Energy Systems is a pivotal reference source for the latest academic material on the integration of supercritical fluids into contemporary energy-related applications. Highlighting innovative discussions on topics such as renewable energy, fluid dynamics, and heat and mass transfer, this book is ideally designed for researchers, academics, professionals, graduate students, and practitioners interested in the latest trends in energy conversion.


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