About this Research Topic
Big data science is interdisciplinary by nature: it is located at the intersection of a number of scientific disciplines, including computer science, mathematics, statistics, information science, geography, biology, medicine, neuroscience, and environmental science. Rooted in big data science, this Research Topic seeks to examine data in a variety of forms, extract critical knowledge from them, and disclose that knowledge as actionable intelligence. The Topic's ultimate goal is to generate insights and innovative methods for strategic policy development and decision making for businesses and organizations.
The article collection will explore data science, machine learning, decision-making, and knowledge discovery innovative methodologies and processes that will assist organizations in making smart decisions. The Research Topic is expected to drive theoretical and practical innovation in artificial intelligence via data mining and knowledge discovery, pattern recognition, machine learning, reinforcement learning, computer vision, multimedia, recommender systems, and digital technology; with the aim of influencing research policy development and implementations.
Implementations include, but are not limited to, intelligent machines for smarter business decisions; internet video and face detection and recognition; product recommendation and prediction algorithms; model-driven and data-driven decision support systems; prediction and early warning systems; fuzzy transfer learning; concept drift; and multi-criteria and multi-level decision-making—all powerful software tools that organizations can use to support decision-making.
Specific topics of interest include, but are not limited, to the following:
• decision support systems for smart policymaking
• application of AI for strategic public policy development and management
• application of AI for strategic business management in science and technology
• applications of AI for science and technology business policy development and management
• the impact of AI on business policy and strategic management
• the impact of AI on decision making in the science and technology industry
• assessment of various AI techniques and implementations for improving business decision making in science and technology.
The article collection will explore data science, machine learning, decision-making, and knowledge discovery innovative methodologies and processes that will assist organizations in making smart decisions. The Research Topic is expected to drive theoretical and practical innovation in artificial intelligence via data mining and knowledge discovery, pattern recognition, machine learning, reinforcement learning, computer vision, multimedia, recommender systems, and digital technology; with the aim of influencing research policy development and implementations.
Implementations include, but are not limited to, intelligent machines for smarter business decisions; internet video and face detection and recognition; product recommendation and prediction algorithms; model-driven and data-driven decision support systems; prediction and early warning systems; fuzzy transfer learning; concept drift; and multi-criteria and multi-level decision-making—all powerful software tools that organizations can use to support decision-making.
Specific topics of interest include, but are not limited, to the following:
• decision support systems for smart policymaking
• application of AI for strategic public policy development and management
• application of AI for strategic business management in science and technology
• applications of AI for science and technology business policy development and management
• the impact of AI on business policy and strategic management
• the impact of AI on decision making in the science and technology industry
• assessment of various AI techniques and implementations for improving business decision making in science and technology.
Keywords: Decision-making, Strategic policy development, Artificial Intelligence, Big data, Data Science, Machine learning, Smart decisions
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
