Introductory Concepts In Information Science
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Introduction to Information Science
This landmark textbook takes a whole subject approach to Information Science as a discipline. Introduced by leading international scholars and offering a global perspective on the discipline, this is designed to be the standard text for students worldwide. The authors' expert narrative guides you through each of the essential building blocks of information science offering a concise introduction and expertly chosen further reading and resources. Critical topics covered include: foundations: - concepts, theories and historical perspectives - organising and retrieving information - information behaviour, domain analysis and digital literacies - technologies, digital libraries and information management - information research methods and informetrics - changing contexts: information society, publishing, e-science and digital humanities - the future of the discipline. Readership: Students of information science, information and knowledge management, librarianship, archives and records management worldwide. Students of other information-related disciplines such as museum studies, publishing, and information systems and practitioners in all of these disciplines.
Introductory Concepts in Information Science
Presents a unique and carefully researched introduction to the practical and theoretical concepts of information science and examines the impact of the Information Age on society and its institutions. Drawing on recent research into the field, as well as from scholarly and trade publications, the monograph provides a brief history of information science and coverage of key topics, including communications and cognition, information retrieval, bibliometrics, modeling, economics, information policies, and the impact of information technology on modern management. An essential volume for graduate students, practitioners, and any professional who needs a solid grounding in the field of information science.
Introduction to Data Science
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.