Transparent Data Mining For Big And Small Data

This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

Financial technology is rapidly changing and shaping financial services and markets. These changes are considered making the future of finance a digital one.This Handbook analyses developments in the financial services, products and markets that are being reshaped by technologically driven changes with a view to their policy, regulatory, supervisory and other legal implications. The Handbook aims to illustrate the crucial role the law has to play in tackling the revolutionary developments in the financial sector by offering a framework of legally enforceable principles and values in which such innovations might take place without threatening the acquis of financial markets law and more generally the rule of law and basic human rights. With contributions from international leading experts, topics will include: Policy, High-level Principles, Trends and Perspectives Fintech and Lending Fintech and Payment Services Fintech, Investment and Insurance Services Fintech, Financial Inclusion and Sustainable Finance Cryptocurrencies and Cryptoassets Markets and Trading Regtech and Suptech This Handbook will be of great relevance for practitioners and students alike, and a first reference point for academics researching in the fields of banking and financial markets law.

This book presents the outcomes of the 2022 4th International Conference on Cyber Security Intelligence and Analytics (CSIA 2022), an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber-security, particularly focusing on threat intelligence, analytics, and countering cyber-crime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings and novel techniques, methods and applications on all aspects of cyber-security intelligence and analytics. Due to COVID-19, authors, keynote speakers and PC committees will attend the conference online.

Winner of two Outstanding Book Awards from the Association of Educational Communications and Technology (Culture, Learning, & Technology and Systems Thinking & Change divisions)! Rapid advancements in our ability to collect, process, and analyze massive amounts of data along with the widespread use of online and blended learning platforms have enabled educators at all levels to gain new insights into how people learn. Responsible Analytics and Data Mining in Education addresses the thoughtful and purposeful navigation, evaluation, and implementation of these emerging forms of educational data analysis. Chapter authors from around the world explore how data analytics can be used to improve course and program quality; how the data and its interpretations may inadvertently impact students, faculty, and institutions; the quality and reliability of data, as well as the accuracy of data-based decisions; ethical implications surrounding the collection, distribution, and use of student-generated data; and more. This volume unpacks and explores this complex issue through a systematic framework whose dimensions address the issues that must be considered before implementation of a new initiative or program.

How can you be an ethical corporate citizen in an increasingly complex, multiple-stakeholder world? This is the most pressing question facing businesses today, small and large, local and global. Business Ethics, fifth edition, is a thorough yet accessible exploration of the main ethical theories and how these apply to major stakeholders facing this question.Written from a truly international perspective and supported by diverse and innovative learning features, this book provides the tools and concepts necessary to understand and effectively manage ethical challenges wherever you are in the world.NEW TO THIS EDITIONProfessor Laura Spence and Dr Sarah Glozer join the author team, bringing fresh perspectives and new expertisePractitioner Spotlights feature prominent businesswomen and men, discovering the ethical challenges they face at work and also the skills they employ to tackle themEthics in Action boxes have been substantially refreshed, with new examples exploring ethical considerations at organizations such as Nudie, Jeans Co., Brewdog, and indigenous Bangladeshi tanneries, as well as complex issues including digital currency, modern slavery, and Big DataNew Case Studies address the latest developments in the business environment, such as the sharing economy and sustainability.This title is available as an eBook. Please contact your Learning Resource Consultant for more information.

This book includes selected papers presented at International Conference on Computational Intelligence, Data Science and Cloud Computing (IEM-ICDC) 2020, organized by the Department of Information Technology, Institute of Engineering & Management, Kolkata, India, during 25-27 September 2020. It presents substantial new research findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.

Interest in anthropology and ethnography has been an ongoing feature of organizational research and pedagogy; this book provides a key reference text that pulls together the different ways in which anthropology infuses the study of organizations, both epistemologically and methodologically. The volume hosts key scholars and experts within the fields of Organizational Anthropology, Organizational Ethnography, Organizational Studies and Qualitative Research. The book provides a combination of methodological guidelines, exemplars and epistemological reflection. It includes methodological viewpoints, ethnographic journeys within organizations as well as beyond organizations, and individual reflections on challenges faced by organizational ethnographers. This book is aimed at PhD, master and advanced undergraduate students and researchers across disciplines, especially those who are engaged with general management, organizational behaviour, strategy and anthropological/ethnographic issues.

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.