ＫＩＰＩＫＩＰＩKIPO’s plan of establishing anddisseminating patent data
PIFC | February 2022

The Value of Patent-related Data

Patents are the result of R&D and acollection of information on the latest globaltechnologies. In addition, patent data is built

Global Patent Applications
1,997

2,158

2,357

2,556

2,672

2013

2014

2,878

3,117

3,161

3,325

3,224

2016

2017

2018

2019

and managed according to international
standards, which enables its effectiveutilization.

2010

2011

2012

2015

 Possible to analyze competitiveness by industry and technical fieldex) Company A’s patent applications in the LCD area overtook Company B’s in 2011, and 7
years later, in 2018, the market share of these companies has been also reversed.

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ＫＩＰＩＫＩＰＩThe Value of Patent-related Data
 Fast and efficient R&D support for companies when using experimental dataex) Correlation Analysis between composition ratio and properties of compounds
using experimental data from patent literature The most valuable intangible asset and value-added creation
90% of the market value of S&P 500
companies is intangible assets.
* Reference: Intangible Asset Market Value Study (2021.3.,Ocean Tomo), Intangible Assets Financial Statement Impact
Comparison Report (2019.4., Ponemon Institute)2

1. Construction of Patent Database for Corporate Valuation and R&D Support
 Expanding scope of citation DB among domestic patent examination procedure information(As-Is) Patents cited by the examiner⇒ (To-Be) Patents browsed and referenced in the examination process Building a DB for key indicators to be used for value evaluation
Building a quantitative data on indicators used for patent valuation, such as the number ofcitations, family patents, claims, and information on transfer of rights32ＫＩＰＩ

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Construction of Patent Database for Corporate Valuation and R&D Support
 Text conversion of experimental data is provided for immediate use in R&D
Increase R&D efficiency in fields such as vaccines, new drugs, and new materials
Provision of a patent & non-patent literature integrated search environment by assigning CPC
codes to non-patent literature
Developed an AI-based CPC code classification system to automatically assign CPC codes to non-patent
literature
Non Patent Literature

AI training dataAI classification system Application to NPL4

2. Build the Foundation for the Analysis of Patent Competitiveness by industry
 A mapping table that interconnects industry standard classification and patentclassification to provide a quick way to analyze patent trends by industry< KSIC-CPC mapping table >< Patent applications in Semiconductor manufacturing field >

KSIC

CPC

Semiconductor manufacturing

G11C, H01L

Electronic Component manufacturing

B05D, B81B, B81C, B82B, ...

30,000Computer manufacturing

G06J, G06K, B41J 2/, ...

20,000Communication Device manufacturing

G03H, H01P, H01Q, H01S, ...

Video Equipment manufacturing

G10L, H03J, H04H, H04N, ...

…

…

45,00040,00035,00025,00015,00010,0005,00002016

2017
CNIPA

EPO

2018
JPO

2019
KIPO

2020
USPTO

 DB of key research personnel for each industry
Establishing a pool of key human resources for each industry by standardizing the inventor informationof patents and linking with researcher information in non-patent literature including papers
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3. Expanding the Scope of Overseas Patent Data Expansion of patent data acquisition in emerging markets and enhancement of usability
Expanding patent data exchange activities centered on emerging countries and resolvinglanguage barriers by providing text conversion and machine translation services for overseas
patent data in the form of images.
< Conversion of image data to text >< Machine translation service >(Applicant) JANSSENSCIENCES IRELAND
UNLIMITED COMPANY(Inventor) LANÇOIS, DavidFrancis Alain...

 Securing transfer ownership data of domestic and overseas patent
Extract information related to the transfer of ownership of patent obtained from overseas,
add it to the database and use it as basic data for industry-specific patent trend analysis

6Thank you!

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