Artificial Intelligence And Visualization Advancing Visual Knowledge Discovery
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Artificial Intelligence And Visualization Advancing Visual Knowledge Discovery
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Author : Boris Kovalerchuk
language : en
Publisher: Springer Nature
Release Date : 2024-04-24
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 2024-04-24 with Computers 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.
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 In Hci
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Author : Helmut Degen
language : en
Publisher: Springer Nature
Release Date : 2025-07-02
Artificial Intelligence In Hci written by Helmut Degen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-02 with Computers categories.
The four-volume set LNAI 15819–15822 constitutes the thoroughly refereed proceedings of the 6th International Conference on Artificial Intelligence in HCI, AI-HCI 2025, held as part of the 27th International Conference, HCI International 2025, which took place in Gothenburg, Sweden, June 22-17, 2025. The total of 1430 papers and 355 posters included in the HCII 2025 proceedings was carefully reviewed and selected from 7972 submissions. The papers have been organized in topical sections as follows: Part I: Trust and Explainability in Human-AI Interaction; User Perceptions, Acceptance, and Engagement with AI; UX and Socio-Technical Considerations in AI Part II: Bias Mitigation and Ethics in AI Systems; Human-AI Collaboration and Teaming; Chatbots and AI-Driven Conversational Agents; AI in Language Processing and Communication. Part III: Generative AI in HCI; Human-LLM Interactions and UX Considerations; Everyday AI: Enhancing Culture, Well-Being, and Urban Living. Part IV: AI-Driven Creativity: Applications and Challenges; AI in Industry, Automation, and Robotics; Human-Centered AI and Machine Learning Technologies.
Navigating Ai And The Metaverse In Scientific Research
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Author : Al Aqad, Mohammed H.
language : en
Publisher: IGI Global
Release Date : 2025-04-24
Navigating Ai And The Metaverse In Scientific Research written by Al Aqad, Mohammed H. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Science categories.
The rapid advancements in artificial intelligence (AI) and the emergence of the metaverse have transformed various fields of research, offering unprecedented opportunities for innovation, collaboration, and exploration. These technologies have enabled researchers to simulate complex phenomena, analyze large datasets with precision, and create immersive environments for experimental studies. As AI algorithms continue to evolve and the metaverse becomes more accessible, the scientific community is poised to leverage these tools to push the boundaries of traditional research methodologies. However, this paradigm shift also introduces new challenges, including ethical concerns, data security, and the need for interdisciplinary expertise. Navigating AI and the Metaverse in Scientific Research raises questions about data privacy, algorithmic bias, and the ethical implications of automated decision-making. It explores how AI and the metaverse can be leveraged for research and development in various sectors and assesses the implications of these technologies on research ethics, education, and public policy. Covering topics such as academic standards, personalized learning experiences, and research integrity, this book is an excellent resource for industry practitioners, policymakers, educators, professionals, researchers, scholars, academicians, and more.
Advanced Visual Interfaces Supporting Artificial Intelligence And Big Data Applications
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Author : Thoralf Reis
language : en
Publisher: Springer Nature
Release Date : 2021-02-02
Advanced Visual Interfaces Supporting Artificial Intelligence And Big Data Applications written by Thoralf Reis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-02 with Computers categories.
This book constitutes the thoroughly refereed post-workshop proceedings of the AVI 2020 Workshop on Road Mapping Infrastructures for Artificial Intelligence Supporting Advanced Visual Big Data Analysis, AVI-BDA 2020, held in Ischia, Italy, in June 2020, and the Second Italian Workshop on Visualization and Visual Analytics, held in Ischia, Italy, in September 2020. The 14 regular papers in this volume present topics such as big data collection, management and curation; big data analytics; big data interaction and perception; big data insight and effectuation; configuration and management of big data storage and compute infrastructures, services, and tools; advanced visual interaction in big data applications; user empowerment and meta design in big data applications; prediction and automation of big data analysis workflows; as well as data visualization; information visualization; visual analytics; infographics; and design.
Game Data Science
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Author : Magy Seif El-Nasr
language : en
Publisher: Oxford University Press
Release Date : 2021
Game Data Science written by Magy Seif El-Nasr and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Computers categories.
Games Data Science delivers an excellent introduction to this new domain and provides the definitive guide to methods and practices of computer science, analytics, and data science as applied to video games.
Geographic Data Mining And Knowledge Discovery
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Author : Harvey J. Miller
language : en
Publisher: CRC Press
Release Date : 2009-05-27
Geographic Data Mining And Knowledge Discovery written by Harvey J. Miller and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-27 with Computers categories.
The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has bee
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.
Machine Learning For Health Informatics
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2016-12-09
Machine Learning For Health Informatics written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-09 with Computers categories.
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
Interactive Knowledge Discovery And Data Mining In Biomedical Informatics
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2014-06-17
Interactive Knowledge Discovery And Data Mining In Biomedical Informatics written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-17 with Computers categories.
One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of = 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human–Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning./ppThis state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security.