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Anticipating Future Innovation Pathways Through Large Data Analysis

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Cover of 'Anticipating Future Innovation Pathways Through Large Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 FTA as Due Diligence for an Era of Accelerated Interdiction by an Algorithm-Big Data Duo
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    Chapter 2 A Conceptual Framework of Tech Mining Engineering to Enhance the Planning of Future Innovation Pathway (FIP)
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    Chapter 3 Profile and Trends of FTA and Foresight
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    Chapter 4 Recent Trends in Technology Mining Approaches: Quantitative Analysis of GTM Conference Proceedings
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    Chapter 5 Anticipating Future Pathways of Science, Technologies, and Innovations: (Map of Science)2 Approach
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    Chapter 6 Towards Foresight 3.0: The HCSS Metafore Approach—A Multilingual Approach for Exploring Global Foresights
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    Chapter 7 Using Enhanced Patent Data for Future-Oriented Technology Analysis
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    Chapter 8 Innovation and Design Process Ontology
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    Chapter 9 Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis, and Term Clumping Analysis
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    Chapter 10 Identifying Targets for Technology Mergers and Acquisitions Using Patent Information and Semantic Analysis
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    Chapter 11 Identifying Technological Topic Changes in Patent Claims Using Topic Modeling
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    Chapter 12 Semi-automatic Technology Roadmapping Composing Method for Multiple Science, Technology, and Innovation Data Incorporation
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    Chapter 13 Generating Futures from Text—Scenario Development Using Text Mining
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    Chapter 14 Additive Manufacturing: Importance and Challenges for Latin America
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    Chapter 15 The Application of Social Network Analysis: Case of Smart Roofing
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    Chapter 16 Building a View of the Future of Antibiotics Through the Analysis of Primary Patents
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    Chapter 17 Combining Scientometrics with Patent-Metrics for CTI Service in R&D Decision-Making: Practices of National Science Library of CAS
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    Chapter 18 Tech Mining for Emerging STI Trends Through Dynamic Term Clustering and Semantic Analysis: The Case of Photonics
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12 X users
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Title
Anticipating Future Innovation Pathways Through Large Data Analysis
Published by
Springer International Publishing, January 2016
DOI 10.1007/978-3-319-39056-7
ISBNs
978-3-31-939054-3, 978-3-31-939056-7
Editors

Tugrul U. Daim, Denise Chiavetta, Alan L. Porter, Ozcan Saritas

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X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 5%
Student > Master 2 5%
Librarian 1 3%
Student > Ph. D. Student 1 3%
Student > Bachelor 1 3%
Other 2 5%
Unknown 31 78%
Readers by discipline Count As %
Business, Management and Accounting 2 5%
Social Sciences 2 5%
Agricultural and Biological Sciences 1 3%
Economics, Econometrics and Finance 1 3%
Computer Science 1 3%
Other 0 0%
Unknown 33 83%