Big Data and Artificial Intelligence
Volume III
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The Topic "Big Data and Artificial Intelligence" explores the transformative impact of AI and Big Data across diverse domains, highlighting their role as catalysts for innovation, decision-making, and business model evolution. This reprint presents cutting-edge research, covering the full spectrum of AI and Big Data applications, from theoretical foundations to real-world implementations. Key topics include enabling technologies such as machine learning, neural networks, natural language processing, AI agents, analytics, and distributed computing. Methodological advancements, strategic framewo...
The Topic "Big Data and Artificial Intelligence" explores the transformative impact of AI and Big Data across diverse domains, highlighting their role as catalysts for innovation, decision-making, and business model evolution. This reprint presents cutting-edge research, covering the full spectrum of AI and Big Data applications, from theoretical foundations to real-world implementations. Key topics include enabling technologies such as machine learning, neural networks, natural language processing, AI agents, analytics, and distributed computing. Methodological advancements, strategic frameworks, and models are examined, addressing areas such as sustainable development, industry innovation, ethical considerations, and social impact. Additionally, the collection showcases best practices, R&D project outcomes, and industry-government collaborations, offering valuable insights into the latest developments in AI-driven decision-making and data ecosystems. Edited by Prof. Miltiadis D. Lytras and Prof. Andreea Claudia Serban, this reprint compiles high-quality contributions from leading researchers and practitioners, providing a comprehensive resource for academics, industry experts, and policymakers interested in the evolving landscape of artificial intelligence and Big Data. The participating journals include Big Data and Cognitive Computing, Future Internet, Information, Remote Sensing, and Sustainability.
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