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Web and Big Data, Jie Shao; Man Lung Yiu; Masashi Toyoda; Dongxiang


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Цена: 10340.00р.
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При оформлении заказа до: 2025-07-28
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Автор: Jie Shao; Man Lung Yiu; Masashi Toyoda; Dongxiang
Название:  Web and Big Data
ISBN: 9783030260743
Издательство: Springer
Классификация:





ISBN-10: 3030260747
Обложка/Формат: Soft cover
Страницы: 431
Вес: 0.69 кг.
Дата издания: 2019
Серия: Information Systems and Applications, incl. Internet/Web, and HCI
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 115 illustrations, color; 42 illustrations, black and white; xix, 431 p. 157 illus., 115 illus. in color.
Размер: 234 x 156 x 23
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: Third International Joint Conference, APWeb-WAIM 2019, Chengdu, China, August 1–3, 2019, Proceedings, Part II
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This two-volume set, LNCS 11641 and 11642, constitutes the thoroughly refereed proceedings of the Third International Joint Conference, APWeb-WAIM 2019, held in Chengdu, China, in August 2019. The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions.


Linear Algebra and Learning from Data

Автор: Strang Gilbert
Название: Linear Algebra and Learning from Data
ISBN: 0692196382 ISBN-13(EAN): 9780692196380
Издательство: Cambridge Academ
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Цена: 9978.00 р.
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Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

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.

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.

Big Data Analytics for Sensor-Network Collected Intelligence

Автор: Hsu, Hui-Huang
Название: Big Data Analytics for Sensor-Network Collected Intelligence
ISBN: 0128093935 ISBN-13(EAN): 9780128093931
Издательство: Elsevier Science
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Цена: 15159.00 р.
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Описание:

Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services.

It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality.

In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation.

Indexing: The books of this series are submitted to EI-Compendex and SCOPUS


  • Contains contributions from noted scholars in computer science and electrical engineering from around the globe
  • Provides a broad overview of recent developments in sensor collected intelligence
  • Edited by a team comprised of leading thinkers in big data analytics
New Directions in Web Data Management 1

Автор: Athena Vakali; Lakhmi C Jain
Название: New Directions in Web Data Management 1
ISBN: 3642266908 ISBN-13(EAN): 9783642266904
Издательство: Springer
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Цена: 30606.00 р.
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Описание: This volume addresses the major issues in Web data management related to technologies and infrastructures, methodologies and techniques as well as applications and implementations. Emphasis is placed on Web engineering and technologies, Web graph managing, searching and querying.

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.

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.

Web and Big Data

Автор: Jie Shao; Man Lung Yiu; Masashi Toyoda; Dongxiang
Название: Web and Big Data
ISBN: 3030260712 ISBN-13(EAN): 9783030260712
Издательство: Springer
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Цена: 10340.00 р.
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Описание: This two-volume set, LNCS 11641 and 11642, constitutes the thoroughly refereed proceedings of the Third International Joint Conference, APWeb-WAIM 2019, held in Chengdu, China, in August 2019. The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions.

Web and Big Data

Автор: Leong Hou U; Haoran Xie
Название: Web and Big Data
ISBN: 3030012972 ISBN-13(EAN): 9783030012977
Издательство: Springer
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Цена: 9222.00 р.
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the First APWeb-WAIM 2018 Workshops, held jointly with the Second International Joint Conference APWeb-WAIM 2018 in Macau, China, in July 2018. The 31 full papers presented were carefully reviewed and selected from 44 submissions. The papers originating from five workshops present cutting-edge ideas, results, experiences, techniques, and tools from all aspects of web data management with the focus on mobile web data analytics; knowledge graph management and analysis; data management and mining on MOOCs; Big data analytics for healthcare; data science.

Data Mining: The Textbook

Автор: С.Aggarwal
Название: Data Mining: The Textbook
ISBN: 3319141414 ISBN-13(EAN): 9783319141411
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.

Web and Big Data

Автор: Shaoxu Song; Matthias Renz; Yang-Sae Moon
Название: Web and Big Data
ISBN: 3319697803 ISBN-13(EAN): 9783319697802
Издательство: Springer
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Цена: 7685.00 р.
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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.


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