Автор: Richard S. Segall, Neha Gupta, Jeffrey S. Cook Название: Handbook of Research on Big Data Storage and Visualization Techniques ISBN: 1522531424 ISBN-13(EAN): 9781522531425 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 547930.00 T Наличие на складе: Невозможна поставка. Описание: The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
Автор: by Laura Po; Nikos Bikakis; Federico Desimoni Название: Linked Data Visualization ISBN: 1681737256 ISBN-13(EAN): 9781681737256 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 53590.00 T Наличие на складе: Нет в наличии. Описание: Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains.
The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens.
This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios.
The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book can serve as a course textbook or a primer for all those interested in LD and data visualization.
Автор: Federico Desimoni, George Papastefanatos, Laura Po, Nikos Bikakis Название: Linked Data Visualization: Techniques, Tools, and Big Data ISBN: 1681737272 ISBN-13(EAN): 9781681737270 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 72070.00 T Наличие на складе: Нет в наличии. Описание: Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains.
The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens.
This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios.
The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book can serve as a course textbook or a primer for all those interested in LD and data visualization.
Автор: Veslava Osinska, Grzegorz Osinski Название: Information Visualization Techniques in the Social Sciences and Humanities ISBN: 1522549900 ISBN-13(EAN): 9781522549901 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 189420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The representation of abstract data and ideas can be a difficult and tedious task to handle when learning new concepts; however, the advances in emerging technology have allowed for new methods of representing such conceptual data.Information Visualization Techniques in the Social Sciences and Humanities is a critical scholarly resource that examines the application of information visualization in the social sciences and humanities. Featuring coverage on a broad range of topics such as social network analysis, complex systems, and visualization aesthetics, this book is geared towards professionals, students, and researchers seeking current research on information visualization.
Автор: Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, R. K. Sharma, Anupam Garg Название: Feature Extraction and Classification Techniques for Text Recognition ISBN: 1799824063 ISBN-13(EAN): 9781799824060 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 257790.00 T Наличие на складе: Нет в наличии. Описание: Presents innovative research on the fusion and hybridization of various features and classifiers for document analysis and recognition. The book highlights a range of topics, including adaptive boosting, writer identification, and signature verification.
Автор: Yim Aldrin, Yu Allen, Chung Claire Название: Matplotlib for Python Developers, Second Edition ISBN: 178862517X ISBN-13(EAN): 9781788625173 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is a useful resource to perform data visualization with Python using the latest version of Matplotlib (2.1.x). You will create a variety of graphs and charts, and embed your plots within different third party tools. By the end of the book, you will build attractive, insightful and powerful visualizations to make better sense of your data.
Автор: Gulati Harish Название: Hands-On SAS For Data Analysis ISBN: 178883982X ISBN-13(EAN): 9781788839822 Издательство: Неизвестно Рейтинг: Цена: 67430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: SAS is one of the leading enterprise tools in the world today when it comes to data management and analysis. It allows for faster, easier processing of data and empowers you to get valuable business insights for effective decision-making. This book will serve as a comprehensive guide you can refer to while preparing for your SAS certification exam.
Автор: Scifo Estelle Название: Hands-On Graph Analytics with Neo4j: Perform graph processing and visualization techniques using connected data across your enterprise ISBN: 1839212616 ISBN-13(EAN): 9781839212611 Издательство: Неизвестно Рейтинг: Цена: 60070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.
This book is aimed to help instructional designers, science game designers, science faculty, lab designers, and content developers in designing interactive learning experiences using emerging technologies and cyberlearning. The proposed solutions are for undergraduate and graduate scientific communication, engineering courses, scientific research communication, and workforce training.
Reviewing across the science education literature reveals various aspects of unresolved challenges or inabilities in the visualization of scientific concepts. Visuospatial thinking is the fundamental part of learning sciences; however, promoting spatial thinking has not been emphasized enough in the educational system (Hegarty, 2014). Cognitive scientists distinguish between the multiple aspects of spatial ability and stresse that various problems or disciplines require different types of spatial skills. For example, the spatial ability to visualize anatomy cross-sections is significantly associated with mental rotation skills. The same is true for physical problems that often deal with spatial representations. However, most of the physics problems are marked by dynamicity, and visualizing dynamicity is inferred by the integrations of different participating components in the system. Therefore, what is needed for learning dynamicity is visualizing the mental animation of static episodes.
This book is a leap into designing framework for using mixed reality (XR) technologies and cyberlearning in communicating advanced scientific concepts. The intention is to flesh out the cognitive infrastructure and visuospatial demands of complex systems and compare them in various contexts and disciplines. The practical implementation of emerging technology can be achieved by foreseeing each XR technology's affordances and mapping those out to the cognitive infrastructure and visuospatial demands of the content under development.
This book is aimed to help instructional designers, science game designers, science faculty, lab designers, and content developers in designing interactive learning experiences using emerging technologies and cyberlearning. The proposed solutions are for undergraduate and graduate scientific communication, engineering courses, scientific research communication, and workforce training.
Reviewing across the science education literature reveals various aspects of unresolved challenges or inabilities in the visualization of scientific concepts. Visuospatial thinking is the fundamental part of learning sciences; however, promoting spatial thinking has not been emphasized enough in the educational system (Hegarty, 2014). Cognitive scientists distinguish between the multiple aspects of spatial ability and stresse that various problems or disciplines require different types of spatial skills. For example, the spatial ability to visualize anatomy cross-sections is significantly associated with mental rotation skills. The same is true for physical problems that often deal with spatial representations. However, most of the physics problems are marked by dynamicity, and visualizing dynamicity is inferred by the integrations of different participating components in the system. Therefore, what is needed for learning dynamicity is visualizing the mental animation of static episodes.
This book is a leap into designing framework for using mixed reality (XR) technologies and cyberlearning in communicating advanced scientific concepts. The intention is to flesh out the cognitive infrastructure and visuospatial demands of complex systems and compare them in various contexts and disciplines. The practical implementation of emerging technology can be achieved by foreseeing each XR technology's affordances and mapping those out to the cognitive infrastructure and visuospatial demands of the content under development.
Автор: Bekos Michael A., Niedermann Benjamin, Nцllenburg Martin Название: External Labeling: Fundamental Concepts and Algorithmic Techniques ISBN: 1636392040 ISBN-13(EAN): 9781636392042 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 53590.00 T Наличие на складе: Нет в наличии. Описание:
This book focuses on techniques for automating the procedure of creating external labelings, also known as callout labelings. In this labeling type, the features within an illustration are connected by thin leader lines (called leaders) with their labels, which are placed in the empty space surrounding the image.
In general, textual labels describing graphical features in maps, technical illustrations (such as assembly instructions or cutaway illustrations), or anatomy drawings are an important aspect of visualization that convey information on the objects of the visualization and help the reader understand what is being displayed.
Most labeling techniques can be classified into two main categories depending on the "distance" of the labels to their associated features. Internal labels are placed inside or in the direct neighborhood of features, while external labels, which form the topic of this book, are placed in the margins outside the illustration, where they do not occlude the illustration itself. Both approaches form well-studied topics in diverse areas of computer science with several important milestones.
The goal of this book is twofold. The first is to serve as an entry point for the interested reader who wants to get familiar with the basic concepts of external labeling, as it introduces a unified and extensible taxonomy of labeling models suitable for a wide range of applications. The second is to serve as a point of reference for more experienced people in the field, as it brings forth a comprehensive overview of a wide range of approaches to produce external labelings that are efficient either in terms of different algorithmic optimization criteria or in terms of their usability in specific application domains. The book mostly concentrates on algorithmic aspects of external labeling, but it also presents various visual aspects that affect the aesthetic quality and usability of external labeling.
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