Representing Scientific Knowledge - The Role of Uncertainty (Paperback, Softcover reprint of the original 1st ed. 2017)

This book is written for anyone who is interested in how a field of research evolves and the fundamental role of understanding uncertainties involved in different levels of analysis, ranging from macroscopic views to meso- and microscopic ones. We introduce a series of computational and visual analytic techniques, from research areas such as text mining, deep learning, information visualization and science mapping, such that readers can apply these tools to the study of a subject matter of their choice. In addition, we set the diverse set of methods in an integrative context, that draws upon insights from philosophical, sociological, and evolutionary theories of what drives the advances of science, such that the readers of the book can guide their own research with their enriched theoretical foundations. Scientific knowledge is complex. A subject matter is typically built on its own set of concepts, theories, methodologies and findings, discovered by generations of researchers and practitioners. Scientific knowledge, as known to the scientific community as a whole, experiences constant changes. Some changes are long-lasting, whereas others may be short lived. How can we keep abreast of the state of the art as science advances? How can we effectively and precisely convey the status of the current science to the general public as well as scientists across different disciplines? The study of scientific knowledge in general has been overwhelmingly focused on scientific knowledge per se. In contrast, the status of scientific knowledge at various levels of granularity has been largely overlooked. This book aims to highlight the role of uncertainties, in developing a better understanding of the status of scientific knowledge at a particular time, and how its status evolves over the course of the development of research. Furthermore, we demonstrate how the knowledge of the types of uncertainties associated with scientific claims serves as an integral and critical part of our domain expertise.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	June 2019
First published:	2017
Authors:	Chaomei Chen • Min Song
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	375
Edition:	Softcover reprint of the original 1st ed. 2017
ISBN-13:	978-3-319-87336-7
Categories:	Books > Computing & IT > Computer programming > Software engineering Books > Reference & Interdisciplinary > Communication studies > Information theory > General Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Promotions
LSN:	3-319-87336-9
Barcode:	9783319873367

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!