Technology Mining: Text Analytics for Evidence-Based Foresight - Tapa dura

 
9783032108487: Technology Mining: Text Analytics for Evidence-Based Foresight
Tapa dura
ISBN 10: 3032108489 ISBN 13: 9783032108487
Editorial: Springer-Verlag GmbH, 2026

Sinopsis

Tech mining is text-oriented analytics that supports decision-making in science, technology, and innovation (ST&I) policy and management in areas including competitive technical intelligence, R&D management, and research evaluation. Presenting selected papers from the 12th Global TechMining Conference (GTM2022), this book covers novel digital information sources such as optimization and integration of 360-degree view in science, economic, political, and social domains; processing methods that accelerate and optimize procedures involving human expertise, such as Delphi; and visualizations and other outputs such as data visualization to provide better communication of research findings. 
Technology Mining: Text-Analytics for Evidence-Based Foresight is an essential guide for a cross-disciplinary network of ST&I policy analysts, software specialists, researchers, technology managers, and students to further advance and adopt textual information in multiple scientific, technology, and business development fields.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Henrique Rego Monteiro da Hora, Ph.D., is a Professor and Deputy Coordinator of the Master in Systems Applied to Engineering and Management (SAEG) program at IFFluminense, and CEO of TEC Campos Incubadora, a technology-based multi-institutional business incubator. He received a BSc in Informatics and an MBA in Production & Systems from CEFET-Campos, an MSc in Industrial Engineering from Universidade Estadual do Norte Fluminense, and his Ph.D. In Industrial Engineering from Universidade Federal Fluminense. His research interests include management of technology transfer, market pull and technology push innovation, decision science, data analytics, technological prospecting, and entrepreneurship and innovation.

Alan Porter, Ph.D., is Director of R&D for Search Technology, Inc., Norcross, GA, producers of VantagePoint and Derwent Data Analyzer software.  He is also Professor Emeritus of Industrial & Systems Engineering, and of Public Policy, at Georgia Tech, wherehe is Co-director of the Program in Science, Technology & Innovation Policy (STIP). Dr. Porter is the author or co-author of some 260 articles and the author or editor of 17 books, including Anticipating Future Innovation Pathways Through Large Data Analysis (Springer, 2016), Tech Mining (Wiley, 2005) and Forecasting and Management of Technology (Wiley, 2011). He co-founded the International Association for Impact Assessment and later served as president. His research interests are focused on developing indicators of technological emergence (with current NSF support).     Denise Chiavetta is a Senior Consultant at Search Technology, Inc., Norcross, GA, a strategy, innovation, and foresight consulting firm. She brings expertise in organizational applications of technology foresight developed over 20 years as a consultant as well as a professional inside Fortune 100 companies and government agencies. She received a BS in Electrical Engineering from Clarkson University and an MS in Studies of the Future from the University of Houston-Clear Lake.

De la contraportada

Tech mining is text-oriented analytics that supports decision-making in science, technology, and innovation (ST&I) policy and management in areas including competitive technical intelligence, R&D management, and research evaluation. Presenting selected papers from the 12th Global TechMining Conference (GTM2022), this book covers novel digital information sources such as optimization and integration of 360-degree view in science, economic, political, and social domains; processing methods that accelerate and optimize procedures involving human expertise, such as Delphi; and visualizations and other outputs such as data visualization to provide better communication of research findings. 

Technology Mining: Text-Analytics for Evidence-Based Foresight is an essential guide for a cross-disciplinary network of ST&I policy analysts, software specialists, researchers, technology managers, and students to further advance and adopt textual information in multiple scientific, technology, and business development fields.
  • Showcases advancing frontiers concerning data, methods, and applications;
  • Examines how tech mining supports decision-making;  
  • Includes contributions from a cross-disciplinary group of global experts.
 

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Editorial
Springer-Verlag GmbH
Año de publicación
2026
Idioma
Inglés
ISBN 10 
3032108489
ISBN 13 
9783032108487
Encuadernación
Tapa dura
Número de páginas
252
Editor
Da Hora Henrique, Porter Alan L., Chiavetta Denise, Zhang Yi
Contacto del fabricante
GPSR Kontakt
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