Patent analytics : transforming IP strategy into intelligence /

Saved in:
Bibliographic Details
Author / Creator:Kim, Jieun.
Imprint:Singapore : Springer, 2021.
Description:1 online resource (217 p.)
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12613882
Hidden Bibliographic Details
Other authors / contributors:Jeong, Buyong.
Kim, Daejung.
ISBN:9789811629303
9811629307
9789811629297
Notes:Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed July 28, 2021).
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.
Other form:Print version: Kim, Jieun Patent Analytics Singapore : Springer Singapore Pte. Limited,c2021 9789811629297
Standard no.:10.1007/978-981-16-2930-3

Similar Items