This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets. Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships. The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data? Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems. The innovations presented are of primary importance for: a. The academic research community b. The ICT market c. Ph.D. students and early stage researchers d. Schools, hospitals, rehabilitation and assisted-living centers e. Representatives from multimedia industries and standardization bodies

The Handbook of Research on Artificial Intelligence, Innovation and Entrepreneurship focuses on theories, policies, practices, and politics of technology innovation and entrepreneurship based on Artificial Intelligence (AI). It examines when, where, how, and why AI triggers, catalyzes, and accelerates the development, exploration, exploitation, and invention feeding into entrepreneurial actions that result in innovation success.

The Ethics of Artificial Intelligence in Education identifies and confronts key ethical issues generated over years of AI research, development, and deployment in learning contexts. Adaptive, automated, and data-driven education systems are increasingly being implemented in universities, schools, and corporate training worldwide, but the ethical consequences of engaging with these technologies remain unexplored. Featuring expert perspectives from inside and outside the AIED scholarly community, this book provides AI researchers, learning scientists, educational technologists, and others with questions, frameworks, guidelines, policies, and regulations to ensure the positive impact of artificial intelligence in learning.

The smart city movement, during the last decade and a half, advocated the built environment and digital technology convergence with the backing of institutional capital and government support. The commitment of a significant number of local governments across the globe, in terms of official smart city policies and initiatives, along with the constant push of global technology giants, has reinforced the popularity of this movement. This two-volume treatment on smart cities thoroughly explores and sheds light on the prominent elements of the smart city phenomenon and generates a smart city blueprint. This first volume, with its 12 chapters, provides a sound understanding on the key foundations and growth directions of smart city frameworks, technologies, and platforms, with theoretical expansions, practical implications, and real-world case study lessons. The second companion volume offers sophisticated perspectives on the key foundations and directions of smart city policies, communities, and urban futures, with theoretical expansions, practical implications, and real-world case study lessons. This book is an invaluable reference source for urban policymakers, managers, planners, practitioners, and many others, particularly to benefit from it when tackling key urban and societal issues and planning for and delivering smart city solutions. Moreover, the book is also a rich and important repository for scholars and research and undergraduate students as it communicates the complex smart city phenomenon in an easy to digest form, by providing both the big picture view and specifics of each component of that view. It also appeals to local government agencies and smart city practitioners.

Collaboration in business allows for equitable opportunities and inclusive growth as the economy rises while also permitting partnering organizations to adopt and utilize the latest successful practices and management. However, a market in stasis may require a displacement in order to allow businesses to grow and create new alliances and partnerships toward a shared economy. There is a need for studies that seek to understand the necessity of market disruption and the best supervisory methods for remaining relevant and profitable in a time of change. The Handbook of Research on Managerial Practices and Disruptive Innovation in Asia is an essential reference source that explores successful executive behavior and business operations striving toward a more inclusive economy. Featuring research on topics such as employee welfare, brand orientation, and entrepreneurship, this publication is ideally designed for human resources developers, policymakers, IT specialists, economists, executives, managers, corporate directors, information technologists, and academicians seeking current research focusing on innovative business factors and sustainable economies in Asia.

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Tan Yigitcanlar offers a comprehensive exploration of artificial intelligence’s (AI) role in shaping modern cities. This volume delves into how AI‐driven analytics and big data provide city planners with deeper insights, enabling more informed decision‐making. These insights lead to more efficient resource use, improved public services, and better infrastructure management. In the digital age, AI is revolutionising various sectors, fundamentally altering our approach to problem‐solving and innovation. AI’s transformative power spans industries from healthcare to finance, and now, it is poised to redefine urban planning and development. Urban areas, as the epicentres of human activity and progress, face myriad challenges such as population growth, resource management, environmental sustainability, and infrastructure development. Traditional methods often fall short in addressing these complexities, making the integration of AI an essential frontier. Comprising seven extensive and insightful chapters, this volume bridges the gap between the theoretical potential and practical implementation of AI in urban contexts. It covers foundational concepts of urban AI, examines its applications across different domains, and explores how AI can improve urban life through smarter home technologies and personalised public services. This first volume is complemented by Urban Artificial Intelligence: A Guidebook for Understanding Perceptions and Ethics, which delves into the ethical and perceptual dimensions of AI in urban settings. Together, these volumes provide a holistic view of urban artificial intelligence, offering essential insights for urban planners, policymakers, researchers, and anyone interested in the intersection of AI and urban development.

This book presents the latest findings in the areas of digital ecosystem for innovation in agriculture. The book is organized into two sections with thirteen chapters dealing with specialized areas. It provides the reader with an overview of the frameworks and technologies involved in the digitalization of agriculture, as well as the data processing methods, decision-making processes, and innovative services/applications for enabling digital transformations in agriculture. The chapters are written by experts sharing their experiences in lucid language through case studies, suitable illustrations, and tables. The contents have been designed to fulfill the needs of geospatial, data science, agricultural, and environmental sciences of universities, agricultural universities, technological universities, research institutes, and academic colleges worldwide. It helps the planners, policymakers, and extension scientists plan and sustainably manage agriculture and natural resources.

An increasing number of academic libraries worldwide are adopting innovative technologies in creating, organizing, storing, managing, disseminating, preserving, and enhancing access to their vital knowledge in order to adapt to the changing library environment and to stay relevant in the digital world. This transition necessitates a need for best practices and reimagined strategies of implementing innovative technologies to ensure sustainable knowledge access and increase knowledge sharing. Innovative Technologies for Enhancing Knowledge Access in Academic Libraries aims to provide best practices, innovative strategies, theoretical frameworks, conceptual frameworks, and empirical research findings regarding the application of emerging and innovative technologies in managing, preserving, and enhancing knowledge access in academic libraries worldwide. Covering a range of topics such as artificial intelligence, knowledge organization, records management, and library services, this reference work is ideal for librarians, researchers, scholars, practitioners, academicians, instructors, and students.

The two volumes IFIP AICT 459 and 460 constitute the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2015, held in Tokyo, Japan, in September 2015. The 163 revised full papers were carefully reviewed and selected from 185 submissions. They are organized in the following topical sections: collaborative networks; globalization and production management; knowledge based production management; project management, engineering management, and quality management; sustainability and production management; co-creating sustainable business processes and ecosystems; open cloud computing architecture for smart manufacturing and cyber physical production systems; the practitioner's view on "innovative production management towards sustainable growth"; the role of additive manufacturing in value chain reconfiguration and sustainability; operations management in engineer-to-order manufacturing; lean production; sustainable system design for green products; cloud-based manufacturing; ontology-aided production - towards open and knowledge-driven planning and control; product-service lifecycle management: knowledge-driven innovation and social implications; and service engineering.