Web and Big Data, Jie Shao; Man Lung Yiu; Masashi Toyoda; Dongxiang
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 66520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Athena Vakali; Lakhmi C Jain Название: New Directions in Web Data Management 1 ISBN: 3642266908 ISBN-13(EAN): 9783642266904 Издательство: Springer Рейтинг: Цена: 204040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Hu & Kaabouch Название: Big Data Management, Technologies, And Applications ISBN: 1466646993 ISBN-13(EAN): 9781466646995 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 170010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
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) Рейтинг: Цена: 170010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Graham Shawn Et Al Название: Exploring Big Historical Data: The Historian`S Macroscope ISBN: 1783266082 ISBN-13(EAN): 9781783266081 Издательство: World Scientific Publishing Рейтинг: Цена: 85530.00 T 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.
Автор: Graham Shawn Et Al Название: Exploring Big Historical Data: The Historian`S Macroscope ISBN: 1783266376 ISBN-13(EAN): 9781783266371 Издательство: World Scientific Publishing Рейтинг: Цена: 33790.00 T 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.
Автор: Lei Chen; Christian S. Jensen; Cyrus Shahabi; Xiao Название: Web and Big Data, part 1 ISBN: 3319635786 ISBN-13(EAN): 9783319635781 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Shaoxu Song; Matthias Renz; Yang-Sae Moon Название: Web and Big Data ISBN: 3319697803 ISBN-13(EAN): 9783319697802 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Peter Bajcsy; Joe Chalfoun; Mylene Simon Название: Web Microanalysis of Big Image Data ISBN: 3319633597 ISBN-13(EAN): 9783319633596 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Table of Contents. 1
Preface
1 Introduction. 1
1.1 What is image processing pipeline?. 1
1.2 What does web image processing pipeline consist of?. 3
1.3 What are big data microscopy experiments?. 4
1.4 Why are scientists interested in big data microscopy experiments?. 6
1.5 What is the range of applications leveraging image processing pipelines?. 9
1.6 Challenges of big data microscopy experiments. 10
1.7 Tradeoffs before and after digital images are acquired. 12
1.8 Enabling reproducible science from big data microscopy experiments. 14
2 Using Web Image Processing Pipeline for Big Data Microscopy Experiments. 1
2.1 Deploying and Testing the Web Image Processing Pipeline. 2
2.1.1 Types of deployment 4
2.1.2 Deployment of Docker Containers. 6
2.1.3 Deployment recommendations. 7
2.1.4 Test data and computational benchmarks. 8
2.2 Web Image Processing. 10
2.2.1 WIP processing functionality. 10
2.2.2 Examples of WIP usage. 12
2.3 Web Feature Extraction. 15
2.3.1 WFE processing functionality. 17
2.3.2 WFE usage. 19
2.4 Web Statistical Modeling. 21
2.4.1 WSM processing functionality. 23
2.4.2 WSM use case. 24
2.5 Summary. 25
3 Example Use Cases 1
3.1 Cell count and single cell detection. 1
3.1.1 Image processing pipeline. 2
3.1.2 Create a new image collection. 3
3.1.3 Stitching of image tiles. 4
3.1.4 Intensity scaling and pyramid building. 5
3.1.5 Image assembling. 6
3.1.6 Segmentation. 7
3.1.7 Binary image labeling. 8
3.1.8 Feature extraction and single cell detection. 8 3.1.9 Discussion. 9
3.2 Stem cell colony growth computation. 10
3.2.1 Image processing pipeline. 11
3.2.2 Colony tracking and feature extraction
3.2.3 Discussion. 13
3.3 Summary. 15
4 Building Web Image Processing Pipeline for Big Images. 1
4.1 Mapping functionality to information technologies. 1
4.2 The role of each technology in the client-server architecture. 5
4.3 &nbs
Автор: Philipp Cimiano; Oscar Corcho; Valentina Presutti; Название: The Semantic Web: Semantics and Big Data ISBN: 3642382878 ISBN-13(EAN): 9783642382871 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Cai Название: Web and Big Data ISBN: 3319968890 ISBN-13(EAN): 9783319968896 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This two-volume set, LNCS 10987 and 10988, constitutes the thoroughly refereed proceedings of the Second International Joint Conference, APWeb-WAIM 2018, held in Macau, China in July 2018. The 40 full papers presented together with 30 short papers, 6 demonstration papers and 3 keynotes were carefully reviewed and selected from 168 submissions. The papers are organized around the following topics: Text Analysis, Social Networks, Recommender Systems, Information Retrieval, Machine Learning, Knowledge Graph, Database and Web Applications, Data Streams, Data Minging and Application, Query Processing, Big Data and Blockchain.
Автор: Cai Название: Web and Big Data ISBN: 3319968920 ISBN-13(EAN): 9783319968926 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This two-volume set, LNCS 10987 and 10988, constitutes the thoroughly refereed proceedings of the Second International Joint Conference, APWeb-WAIM 2018, held in Macau, China in July 2018. The 40 full papers presented together with 30 short papers, 6 demonstration papers and 3 keynotes were carefully reviewed and selected from 168 submissions. The papers are organized around the following topics: Text Analysis, Social Networks, Recommender Systems, Information Retrieval, Machine Learning, Knowledge Graph, Database and Web Applications, Data Streams, Data Minging and Application, Query Processing, Big Data and Blockchain.
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