The fast-paced world created by the accessibility of consumer information through internet-generated data requires improved information-management platforms. The continuous evaluation and evolution of these systems facilitate enhanced data reference and output.
Optimizing Data and New Methods for Efficient Knowledge Discovery and Information Resources Management is a critical research publication that provides insight into the varied and rapidly changing fields of knowledge discovery and information resource management. Highlighting a range of topics such as datamining, artificial intelligence, and risk assessment, this book is essential for librarians, academicians, policymakers, information managers, professionals, and researchers in fields that include artificial intelligence, knowledge discovery, data visualization, big data, and information resources management.
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Susan Swayze holds a Ph.D. in Education from the University of California Los Angeles and an M.B.A. from the Duke University Fuqua School of Business. She is an accomplished scholar who leverages her qualitative and quantitative research expertise to develop courses, teach adult students, and advise dissertation research. Dr. Swayze’s research interests include psychological capital, diversity and inclusion, adult learning in online environments, and data-driven decision-making. She also provides interview and survey-based consulting services in the areas of program evaluation and organizational development. During the past 10 years, Dr. Swayze has produced over 100 scholarly works―including edited books, journal articles, book chapters, conference presentations, and workshops.
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