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Web and Big Data, Shaoxu Song; Matthias Renz; Yang-Sae Moon


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Автор: Shaoxu Song; Matthias Renz; Yang-Sae Moon
Название:  Web and Big Data
ISBN: 9783319697802
Издательство: Springer
Классификация:



ISBN-10: 3319697803
Обложка/Формат: Paperback
Страницы: 248
Вес: 0.40 кг.
Дата издания: 09.11.2017
Серия: Information Systems and Applications, incl. Internet/Web, and HCI
Язык: English
Издание: 1st ed. 2017
Иллюстрации: 83 illustrations, black and white; xii, 253 p. 83 illus.
Размер: 234 x 156 x 15
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: APWeb-WAIM 2017 International Workshops: MWDA, HotSpatial, GDMA, DDC, SDMA, MASS, Beijing, China, July 7-9, 2017, Revised Selected Papers
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book constitutes the thoroughly refereed post-conference proceedings of the First APWeb-WAIM 2017 Workshops, held jointly with the First International Joint Conference APWeb-WAIM 2017, held in Beijing, China, in July 2017.


Big Data Analytics and Knowledge Discovery

Автор: Madria
Название: Big Data Analytics and Knowledge Discovery
ISBN: 3319439456 ISBN-13(EAN): 9783319439457
Издательство: Springer
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Цена: 8106.00 р.
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Описание: The papers are organized in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data Learning and Security, Graph Databases and Data Warehousing, Data Intelligence and Technology.

Data Mining and Big Data

Автор: Tan
Название: Data Mining and Big Data
ISBN: 3319409727 ISBN-13(EAN): 9783319409726
Издательство: Springer
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Цена: 11179.00 р.
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Описание: The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016. The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions.

Performance Evaluation and Benchmarking. Traditional - Big Data - Internet of Things

Автор: Raghunath Nambiar; Meikel Poess
Название: Performance Evaluation and Benchmarking. Traditional - Big Data - Internet of Things
ISBN: 3319543334 ISBN-13(EAN): 9783319543338
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Innovative techniques for evaluation, measurement and characterization of complex systems.- Novel ideas and methodologies in permforance evaluation, measurement, and characterization.

Web and Big Data, part 1

Автор: Lei Chen; Christian S. Jensen; Cyrus Shahabi; Xiao
Название: Web and Big Data, part 1
ISBN: 3319635786 ISBN-13(EAN): 9783319635781
Издательство: Springer
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Цена: 12577.00 р.
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Описание: This two -volume set, LNCS 10366 and 10367, constitutes the thoroughly refereed proceedings of the First International Joint Conference, APWeb-WAIM 2017, held in Beijing, China in July 2017. The 44 full papers presented together with 32 short papers and 10 demonstrations papers were carefully reviewed and selected from 240 submissions.

The Semantic Web: Semantics and Big Data

Автор: Philipp Cimiano; Oscar Corcho; Valentina Presutti;
Название: The Semantic Web: Semantics and Big Data
ISBN: 3642382878 ISBN-13(EAN): 9783642382871
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the refereed proceedings of the 10th Extended Semantic Web Conference, ESWC 2013, held in Montpellier, France, in May 2013. mobile Web, sensors and semantic streams; social Web and Web science; cognition and semantic Web; The book also includes 17 PhD papers presented at the PhD Symposium.

Cases On Open-Linked Data And Semantic Web Applications

Автор: Ord??ez De Pablos, Lytras, Tenny
Название: Cases On Open-Linked Data And Semantic Web Applications
ISBN: 1466628278 ISBN-13(EAN): 9781466628274
Издательство: Mare Nostrum (Eurospan)
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Цена: 25502.00 р.
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Описание: With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of these elements leads to the creation of data commons called semantic web. <br><br><em>Cases on Open-Linked Data and Semantic Web Applications</em> brings together new theories, research findings and case studies which cover the recent developments and approaches towards applied open linked data and semantic web in the context of information systems. By enhancing the understanding of open linked data in business, science and information technologies, this reference source aims to be useful for academics, researchers, and practitioners. With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of these elements leads to the creation of data commons called semantic web.

Big Data Management, Technologies, And Applications

Автор: Hu & Kaabouch
Название: Big Data Management, Technologies, And Applications
ISBN: 1466646993 ISBN-13(EAN): 9781466646995
Издательство: Mare Nostrum (Eurospan)
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Цена: 25502.00 р.
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Описание: Due to the tremendous amount of data generated daily from fields such as business, research, and sciences, big data is everywhere. Therefore, alternative management and processing methods have to be created to handle this complex and unstructured data size.Big Data Management, Technologies, and Applications discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data. With its prevalence, this collection of articles on big data methodologies and technologies are beneficial for IT workers, researchers, students, and practitioners in this timely field.

Exploring Big Historical Data: The Historian`S Macroscope

Автор: Graham Shawn Et Al
Название: Exploring Big Historical Data: The Historian`S Macroscope
ISBN: 1783266082 ISBN-13(EAN): 9781783266081
Издательство: World Scientific Publishing
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Цена: 12830.00 р.
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Описание: The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors introduce the many different tools and developing approaches in Big Data for historical and humanistic scholarship, show how to use them, what to be wary of, and discuss the kinds of questions and new perspectives this new macroscopic perspective opens up. Authored 'live' online with ongoing feedback from the wider digital history community, Exploring Big Historical Data breaks new ground and sets the direction for the conversation into the future. It represents the current state-of-the-art thinking in the field and exemplifies the way that digital work can enhance public engagement in the humanities.Exploring Big Historical Data should be the go-to resource for undergraduate and graduate students confronted by a vast corpus of data, and researchers encountering these methods for the first time. It will also offer a helping hand to the interested individual seeking to make sense of genealogical data or digitized newspapers, and even the local historical society who are trying to see the value in digitizing their holdings.The companion website to Exploring Big Historical Data can be found at www.themacroscope.org/. On this site you will find code, a discussion forum, essays, and datafiles that accompany this book.

Exploring Big Historical Data: The Historian`S Macroscope

Автор: Graham Shawn Et Al
Название: Exploring Big Historical Data: The Historian`S Macroscope
ISBN: 1783266376 ISBN-13(EAN): 9781783266371
Издательство: World Scientific Publishing
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Цена: 5069.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors introduce the many different tools and developing approaches in Big Data for historical and humanistic scholarship, show how to use them, what to be wary of, and discuss the kinds of questions and new perspectives this new macroscopic perspective opens up. Authored 'live' online with ongoing feedback from the wider digital history community, Exploring Big Historical Data breaks new ground and sets the direction for the conversation into the future. It represents the current state-of-the-art thinking in the field and exemplifies the way that digital work can enhance public engagement in the humanities.Exploring Big Historical Data should be the go-to resource for undergraduate and graduate students confronted by a vast corpus of data, and researchers encountering these methods for the first time. It will also offer a helping hand to the interested individual seeking to make sense of genealogical data or digitized newspapers, and even the local historical society who are trying to see the value in digitizing their holdings.The companion website to Exploring Big Historical Data can be found at www.themacroscope.org/. On this site you will find code, a discussion forum, essays, and datafiles that accompany this book.

Advanced Visual Interfaces. Supporting Big Data Applications

Автор: Bornschlegl
Название: Advanced Visual Interfaces. Supporting Big Data Applications
ISBN: 3319500694 ISBN-13(EAN): 9783319500690
Издательство: Springer
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Цена: 5870.00 р.
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Описание:

IVIS4BigData: A Reference Model for Advanced Visual Interfaces Supporting Big Data Analysis in Virtual Research Environments.- Engineering Study of Tidal Stream Renewable Energy Generation and Visualization: Issues of Process Modelling and Implementation.- Cost effective visualization of research data for cognitive development using mobile Augmented Reality.- Visualizing Next-Generation Sequencing Cancer Data Sets with Cloud Computing.- SenseCare: Towards an Experimental Platform for Home-Based, Visualisation of Emotional States of People with Dementia.- Toward Interactive Visualization of Results from Domain-Specific Text Analytics.- Towards Synchronizing Data Sources and Information Visualizations in Virtual Research Environments.- Visual analytics and mining over Big Data.- A Meta-design Approach to Support Information Access and Manipulation in Virtual Research Environments.

Machine Learning, Optimization, and Big Data

Автор: Pardalos
Название: Machine Learning, Optimization, and Big Data
ISBN: 3319514687 ISBN-13(EAN): 9783319514680
Издательство: Springer
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Цена: 9224.00 р.
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Описание: This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions.

Big Data Computing and Communications

Автор: Wang
Название: Big Data Computing and Communications
ISBN: 3319425528 ISBN-13(EAN): 9783319425528
Издательство: Springer
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Цена: 8944.00 р.
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Описание: This book constitutes the proceedings of the Second International Conference on Big Data Computing and Communications, BigCom 2016, held in Shenyang, China, in July 2016.


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