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Introduction.- Part I: Data. Emergence of Patent Big Data.- Chapter 1 Patent as Big Data?.- Chapter 2 Significant Points in the History of Patents.- Chapter 3 Understanding Patent Data.- Part II. Network: Patent Network Visualization.- Chapter 4 Prelude to the Era of Patent Data Visualization.- Chapter 5 Effective Visual Mapping of Patent Data.- Chapter 6 The Power of Patent Citation Networks.- Chapter 7 A Complete Guide to Patent Network Visualization.- Part III Analytics: Uncharted Corporate Innovations.- Chapter 8 Dyson, From Bladeless Fan to Hair Dryer.- Chapter 9 Bose’s Beyond Sound.- Chapter 10 Innovation Assimilation of M&As in Adobe..- Chapter 11 Network Patterns of Inventor Collaboration: Google vs. Apple.- Chapter 12 Samsung vs. LG, Map of the Competitive Landscape.- Perspectives The Renaissance of Innovation Analytics with AI.- Chapter 13 Is Trademark the First Sparring Partner of AI?.- Chapter 14 New Patent or Not? From Search to Legal Automation.- Chapter 15 Legal Technologies in Action.- Afterword.<div><br></div>

<p><b>Jieun Kim</b> is an associate professor at the Graduate School of Technology and Innovation Management, Hanyang University and co-directs an interdisciplinary research lab -&nbsp;Imagine X lab&nbsp;since 2013.&nbsp;She has a BA in Industrial Design from KAIST (2007) and an MS and PHD in Industrial Engineering from Arts et Métiers ParisTech, Paris (2008/2011), followed by the Leverhulme Research Fellowship (2012) at Royal College of Art in London. She was a visiting associate professor at Human Communication Technologies Lab, University of British Columbia (2020). She served as a general co-chair of ACM TVX 2018 and continued to contribute to many international design and innovation management communities as reviewers and speakers.&nbsp;</p><p><b>Buyong Jeong</b> is a deputy director in the Korean Intellectual Property Office (KIPO). Before joining KIPO in 2015, he worked as a patent attorney at PLUS International IP Law firm (2009–2014). He has been involved in various projects and policies for the Trademark and Design Examination bureau of KIPO. His legal and practical expertise is supported by his academic background, having obtaining bachelor’s and master’s degrees in Industrial design from Korea Advanced Institute of Science and Technology (KAIST). He is the co-author of the Korean chapter for AIPPI Law Series: Design Rights, Functionality and Scope of Protection (by Christopher V. Carani / Wolters Kluwer 2017).&nbsp;</p><p> </p><p><b>Daejung Kim</b> is a data scientist specializing in intellectual property and a senior lecturer at Hankyong National University. He holds his Ph.D. in technology and innovation management from Hanyang University. He is a frequent speaker and consultant in strategic technology and management solutions for many law firms and corporate legal departments.</p><p></p><p></p>

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.

First book on intellectual property for business intelligence, focused on corporate innovation and business value Offers high-level tutorials and case studies for IP-driven innovation in business by using the text and underlying network of patent documents as the direct objects of data analytics and visualization Picture book with high-quality figures of patent gazette, screenshots of software, and patent network visualizations with detailed case studies through an easily understandable format