Integrating Artificial Intelligence And Visualization For Visual Knowledge Discovery
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Integrating Artificial Intelligence And Visualization For Visual Knowledge Discovery
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Author : Boris Kovalerchuk
language : en
Publisher: Springer Nature
Release Date : 2022-06-04
Integrating Artificial Intelligence And Visualization For Visual Knowledge Discovery written by Boris Kovalerchuk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-04 with Technology & Engineering categories.
This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.
Artificial Intelligence Visual Knowledge Discovery And Visual Analytics
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Author : Boris Kovalerchuk
language : en
Publisher: Springer
Release Date : 2023-12-31
Artificial Intelligence Visual Knowledge Discovery And Visual Analytics written by Boris Kovalerchuk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-31 with Technology & Engineering categories.
This book continues a series of Springer publications devoted to the emerging field of Integrated Artificial Intelligence and Machine Learning with Visual Knowledge Discovery and Visual Analytics that combine advances in both fields. Artificial Intelligence and Machine Learning face long-standing challenges of explainability and interpretability that underpin trust. Such attributes are fundamental to both decision-making and knowledge discovery. Models are approximations and, at best, interpretations of reality that are transposed to algorithmic form. A visual explanation paradigm is critically important to address such challenges, as current studies demonstrate in salience analysis in deep learning for images and texts. Visualization means are generally effective for discovering and explaining high-dimensional patterns in all high-dimensional data, while preserving data properties and relations in visualizations is challenging. Recent developments, such as in General Line Coordinates, open new opportunities to address such challenges. This book contains extended papers presented in 2021 and 2022 at the International Conference on Information Visualization (IV) on AI and Visual Analytics, with 18 chapters from international collaborators. The book builds on the previous volume, published in 2022 in the Studies in Computational Intelligence. The current book focuses on the following themes: knowledge discovery with lossless visualizations, AI/ML through visual knowledge discovery with visual analytics case studies application, and visual knowledge discovery in text mining and natural language processing. The intended audience for this collection includes but is not limited to developers of emerging AI/machine learning and visualization applications, scientists, practitioners, and research students. It has multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery, visual analytics, and text and natural language processing. The book provides case examples for future directions in this domain. New researchers find inspiration to join the profession of the field of AI/machine learning through a visualization lens.
Visual Knowledge Discovery And Machine Learning
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Author : Boris Kovalerchuk
language : en
Publisher: Springer
Release Date : 2018-01-17
Visual Knowledge Discovery And Machine Learning written by Boris Kovalerchuk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-17 with Technology & Engineering categories.
This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines Coordinates (GLCs), is accompanied by a set of algorithms for n-D data classification, clustering, dimension reduction, and Pareto optimization. The mathematical and theoretical analyses and methodology of GLC are included, and the usefulness of this new approach is demonstrated in multiple case studies. These include the Challenger disaster, world hunger data, health monitoring, image processing, text classification, market forecasts for a currency exchange rate, computer-aided medical diagnostics, and others. As such, the book offers a unique resource for students, researchers, and practitioners in the emerging field of Data Science.
Information Visualization In Data Mining And Knowledge Discovery
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Author : Usama M. Fayyad
language : en
Publisher: Morgan Kaufmann
Release Date : 2002
Information Visualization In Data Mining And Knowledge Discovery written by Usama M. Fayyad and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
This text surveys research from the fields of data mining and information visualisation and presents a case for techniques by which information visualisation can be used to uncover real knowledge hidden away in large databases.
Artificial Intelligence And Visualization Advancing Visual Knowledge Discovery
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Author : Boris Kovalerchuk
language : en
Publisher: Springer Nature
Release Date :
Artificial Intelligence And Visualization Advancing Visual Knowledge Discovery written by Boris Kovalerchuk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Visual Data Mining
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Author : Simeon Simoff
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-18
Visual Data Mining written by Simeon Simoff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-18 with Computers categories.
The importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.
Machine Learning For Data Science Handbook
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Author : Lior Rokach
language : en
Publisher: Springer Nature
Release Date : 2023-08-17
Machine Learning For Data Science Handbook written by Lior Rokach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-17 with Computers categories.
This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.
Advances In Information And Intelligent Systems
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Author : Zbigniew W. Ras
language : en
Publisher: Springer
Release Date : 2009-10-15
Advances In Information And Intelligent Systems written by Zbigniew W. Ras and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-15 with Computers categories.
The College of Computing and Informatics (CCI) at UNC-Charlotte has three departments: Computer Science, Software and Information Systems, and Bioinformatics and Genomics. The Department of Computer Science offers study in a variety of specialized computing areas such as database design, knowledge systems, computer graphics, artificial intelligence, computer networks, game design, visualization, computer vision, and virtual reality. The Department of Software and Information Systems is primarily focused on the study of technologies and methodologies for information system architecture, design, implementation, integration, and management with particular emphasis on system security. The Department of Bioinformatics and Genomics focuses on the discovery, development and application of novel computational technologies to help solve important biological problems. This volume gives an overview of research done by CCI faculty in the area of Information & Intelligent Systems. Presented papers focus on recent advances in four major directions: Complex Systems, Knowledge Management, Knowledge Discovery, and Visualization. A major reason for producing this book was to demonstrate a new, important thrust in academic research where college-wide interdisciplinary efforts are brought to bear on large, general, and important problems. As shown in the research described here, these efforts need not be formally organized joint undertakings (through parts could be) but are rather a convergence of interests around grand themes.
Data Driven Science For Clinically Actionable Knowledge In Diseases
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Author : Daniel Catchpoole
language : en
Publisher: CRC Press
Release Date : 2023-12-06
Data Driven Science For Clinically Actionable Knowledge In Diseases written by Daniel Catchpoole and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-06 with Medical categories.
Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods, meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory, method, models, design, evaluation and applications in computational and visual analytics in desktop, mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis, including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain, the book demonstrates how analytics influences the domain through improving decision making, specifying diagnostics, selecting the best treatments and generating clinical certainty.
Mapping Scientific Frontiers
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Author : Chaomei Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-07-30
Mapping Scientific Frontiers written by Chaomei Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-30 with Computers categories.
This is an examination of the history and the state of the art of the quest for visualizing scientific knowledge and the dynamics of its development. Through an interdisciplinary perspective this book presents profound visions, pivotal advances, and insightful contributions made by generations of researchers and professionals, which portrays a holistic view of the underlying principles and mechanisms of the development of science. This updated and extended second edition: highlights the latest advances in mapping scientific frontiers examines the foundations of strategies, principles, and design patterns provides an integrated and holistic account of major developments across disciplinary boundaries “Anyone who tries to follow the exponential growth of the literature on citation analysis and scientometrics knows how difficult it is to keep pace. Chaomei Chen has identified the significant methods and applications in visual graphics and made them clear to the uninitiated. Derek Price would have loved this book which not only pays homage to him but also to the key players in information science and a wide variety of others in the sociology and history of science.” – Eugene Garfield “This is a wide ranging book on information visualization, with a specific focus on science mapping. Science mapping is still in its infancy and many intellectual challenges remain to be investigated and many of which are outlined in the final chapter. In this new edition Chaomei Chen has provided an essential text, useful both as a primer for new entrants and as a comprehensive overview of recent developments for the seasoned practitioner.” – Henry Small Chaomei Chen is a Professor in the College of Information Science and Technology at Drexel University, Philadelphia, USA, and a ChangJiang Scholar at Dalian University of Technology, Dalian, China. He is the Editor-in-Chief of Information Visualization and the author of Turning Points: The Nature of Creativity (Springer, 2012) and Information Visualization: Beyond the Horizon (Springer, 2004, 2006).