| Description |
1 online resource (xxii, 206 pages) : color illustrations |
| Contents |
About the Authors -- Abbreviations -- List of Figures -- List of Tables -- 1 Introduction -- 1.1 The Prism of Patent Big Data -- 1.1.1 The Vs to the Patent Big Data Paradigm -- 1.1.2 Coping with Patent Big Data Complexity -- 1.1.3 Harnessing Patent Big Data Analytics to Make a Difference -- 1.2 Overview of the Book -- 1.2.1 Part I: Patent as Data -- 1.2.2 Part II: Network Analytics -- 1.2.3 Part III: Uncover Corporate Innovation with Patent Analytics -- 1.2.4 Part IV: Future Developments with AI -- References -- Part I Patent as Data -- 2 A Brief History of Patents -- 2.1 The Prelude of the Patent System -- 2.2 The First Patent with Claims -- 2.3 The Great Fire and Patent Numbering -- 2.4 Genesis of Citations -- 2.5 Summary -- References -- 3 Understanding Patent Data -- 3.1 Patents, Designs, and Trademarks -- 3.2 A Walk Through of Patent Data Fields |
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3.2.1 INID Codes and Bibliographic Data -- 3.2.2 Patent Numbering System and Kind-Of-Documents -- 3.2.3 Patent Classification System -- 3.2.4 International Patent Classification (INID Code: 51) -- 3.2.5 Cooperative Patent Classification (INID Code: 52) -- 3.3 Same Same, but Different Design Patents -- 3.4 Comprehending Trademark Data -- 3.5 Summary -- References -- 4 Claims, "Legally, Less is More!" -- 4.1 Disentangling Patent Claims -- 4.2 Broad or Narrow: All-Elements Rule -- 4.3 Anatomy of Patent Claims -- 4.4 The Butterfly Effect of Design Patents -- 4.5 Summary -- References -- Part II Network Analytics -- 5 Basic Network Concepts -- 5.1 Why Does Patent Network Analysis Matter? -- 5.2 Basic Concept of Network and Graph Theory -- 5.2.1 Node, Edges, and Attributes -- 5.2.2 Undirected and Directed Network |
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5.2.3 One-Mode and Two-Mode Networks -- 5.2.4 Ego Networks and Complete Networks -- 5.3 Network Metrics -- 5.3.1 Centrality -- 5.3.2 Network Diameter and Density -- 5.3.3 Clustering and Modularity -- 5.4 Summary -- References -- 6 Patent Citations Analysis -- 6.1 The Meaning of Patent Citations -- 6.2 How to Scale up Patent Citation Networks -- 6.3 Pitfalls and Best Practices in Using Patent Citation Data -- 6.4 Summary -- References -- 7 Patent Data Through a Visual Lens -- 7.1 Unexpected Encounters -- 7.2 Six Basic Charts -- 7.2.1 Bar, Line, and Pie Charts -- 7.2.2 Geospatial Visualizations -- 7.2.3 Bubble Charts -- 7.2.4 Treemaps -- 7.3 Network Visualizations -- 7.4 Summary -- References -- 8 How to Study Patent Network Analysis -- 8.1 Research Design -- 8.2 Choosing Network Analysis Tools |
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8.3 Four Practical Steps for Patent Network Analysis -- 8.4 Summary -- References -- Part III Uncover Corporate Innovation with Patent Analytics -- 9 Is Innovation Design-or Technology-Driven? Dyson -- 9.1 Dyson: From Bagless Vacuum Cleaner to Bladeless Hairdryer -- 9.2 Dyson's Patent Citation Analysis: A Complete Network -- 9.3 Technology or Design First? Ego Networks of the Bladeless Fan -- 9.4 Forecasting Dyson's Next Innovation -- 10 Predict Strategic Pivot Points: Bose -- 10.1 Bose's New Neat! Innovation Pivots -- 10.2 Core Innovation: Better Sound -- 10.3 Four Innovation Pivots: Beyond Sound -- 10.3.1 Technology Pivot: Suspension Seats for Vehicles -- 10.3.2 Customer Segment Pivot: High-Tech Cooktops -- 10.3.3 Platform Pivot: Audio AR Sunglasses -- 10.3.4 Zoom-In Pivot: Noise-Masking Sleepbuds -- 10.4 Summary |
| Summary |
Through the prisms of a data scientist, a patent attorney, and a designer, this book demystifies the complexity of patent data and its structure and reveals their hidden connections by employing elaborate data analytics and visualizations using a network map. This book provides a practical guide to introduce and apply patent network analytics and visualization tools in your business. We incorporate case studies from renowned companies such as Apple, Dyson, Adobe, Bose, Samsung and more, to scrutinise how their underlying values of patent network drive innovation in their business. Finally, this book advances readers' perspective of patent gazettes as big data and as a tool for innovation analytics when coupled with Artificial Intelligence |
| Bibliography |
Includes bibliographical references |
| Notes |
Online resource; title from PDF title page (SpringerLink, viewed July 28, 2021) |
| Subject |
Patents -- Data processing
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Patents -- Data processing
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| Form |
Electronic book
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| Author |
Chŏng, Pu-yong, author.
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Kim, Tae-jung (Writer on intellectual property), author.
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| ISBN |
9789811629303 |
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9811629307 |
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