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Author: Tugrul U. Daim
Publisher: Springer
ISBN: 3319390562
Category : Business & Economics
Languages : en
Pages : 366
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Book Description
This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes: The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I). The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests. Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets. Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP. Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.
Author: Tugrul U. Daim
Publisher: Springer
ISBN: 3319390562
Category : Business & Economics
Languages : en
Pages : 366
Get Book Here
Book Description
This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes: The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I). The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests. Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets. Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP. Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 211
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Book Description
Author:
Publisher:
ISBN:
Category : Computer industry
Languages : en
Pages : 192
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Book Description
Author: Management Information Corporation
Publisher:
ISBN:
Category : Computer industry
Languages : en
Pages : 200
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Book Description
Author: Gauri Misra
Publisher: Academic Press
ISBN: 0128172800
Category : Medical
Languages : en
Pages : 188
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Book Description
Data Processing Handbook for Complex Biological Data provides relevant and to the point content for those who need to understand the different types of biological data and the techniques to process and interpret them. The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers. In order to succeed in data processing for biological data sources, it is necessary to master the type of data and general methods and tools for modern data processing. For instance, many labs follow the path of interdisciplinary studies and get their data validated by several methods. Researchers at those labs may not perform all the techniques themselves, but either in collaboration or through outsourcing, they make use of a range of them, because, in the absence of cross validation using different techniques, the chances for acceptance of an article for publication in high profile journals is weakened. Explains how to interpret enormous amounts of data generated using several experimental approaches in simple terms, thus relating biology and physics at the atomic level Presents sample data files and explains the usage of equations and web servers cited in research articles to extract useful information from their own biological data Discusses, in detail, raw data files, data processing strategies, and the web based sources relevant for data processing
Author: Arthur Langer
Publisher: Springer Nature
ISBN: 3031264010
Category : Business & Economics
Languages : en
Pages : 291
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Book Description
Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions that can better predict and respond to the unexpected. Featuring case examples from companies such as Lego, FedEx, General Electric (GE), Pfizer, P&G and more, this book is appropriate for C-level executives engaged in the digital transformation of their firms; entrepreneurs of digital platform companies; and senior software engineers that need to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate-level coursework in data science.
Author: Ulrika Jägare
Publisher: John Wiley & Sons
ISBN: 1119566274
Category : Computers
Languages : en
Pages : 449
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Book Description
All the answers to your data science questions Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the “what” and the “why” of data science and covering what it takes to lead and nurture a top-notch team of data scientists. With this book, you’ll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data. Learn exactly what data science is and why it’s important Adopt a data-driven mindset as the foundation to success Understand the processes and common roadblocks behind data science Keep your data science program focused on generating business value Nurture a top-quality data science team In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value.
Author: OECD
Publisher: OECD Publishing
ISBN: 9264625275
Category :
Languages : en
Pages : 174
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Book Description
This report highlights the important role data can play in creating conditions that improve public services, increase the effectiveness of public spending and inform ethical and privacy considerations. It presents a data-driven public sector framework that can help countries or organisations assess the elements needed for using data to make better-informed decisions across public sectors.
Author: United States. Patent and Trademark Office
Publisher:
ISBN:
Category : Patents
Languages : en
Pages : 1308
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Book Description
Author: Joseph C. Hassab
Publisher: CRC Press
ISBN: 1351094343
Category : Technology & Engineering
Languages : en
Pages : 374
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Book Description
A systematic and integrated account of signal and data processing with emphasis on the distinctive marks of the ocean environment is provided in this informative text. Underwater problems such as space-time processing relations vs. disjointed ones, processing of passive observations vs. active ones, time delay estimation vs. frequency estimation, channel effects vs. transparent ones, integrated study of signal, data, and channel processing vs. separate ones, are highlighted. The book provides the beginner with a concise presentation of the essential concepts, defines the basic computational steps, and gives the mature reader an advanced view of underwater systems and the relationships among their building blocks. It presents the needed topics on applied estimation theory within the underwater systems context. Included are topics in linear and nonlinear filtering, spectral analysis, generalized correlation, cepstrum and complex demodulation, Cramer-Rao Bounds, maximum likelihood, weighted least-squares, Kalman filtering, expert systems, wave propagation and their use, as well as their performance in applications to canonical ocean problems. The applications center on the definition, analysis, and solution implementations to representative underwater signal analysis problems dealing with signals estimation, their location and motion. The potential limitations and pitfalls of the implementations are delineated in homogeneous, noisy, interfering, inhomogeneous, multipath, distortions, and/or dispersive channels.
