A Study on the Comparison of Feature Extraction Methods for Classification of Patent Litigation

Youngho Kim, Junseok Lee, Jiho Kang, Juhyun Lee, Dongsik Jang, Sangsung Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Patents contain detailed information about the developed technology. In addition, patents grant exclusive rights to the developed technology. For this reason, many companies use patents for technology protection. Patent litigation occurs when the operating activities of one company infringe on the scope of the patent rights of another company. When patent litigation occurs, a lot of time and money are consumed. Therefore, it is necessary to prevent patent litigation in advance. In this paper, an appropriate feature extraction method is sought when constructing a model for classifying patent litigation. Principal component analysis and Autoencoder are used to perform the proposed research. The experimental data are those registered with the USPTO as patents related to artificial intelligence. Feature extraction is performed on the quantitative indicators of the collected patents. In addition, performance is measured with various classification algorithms. As a result of the experiment, the classification performance of the method combining Autoencoder and K-Nearest neighbor was good.

Original languageEnglish
Title of host publicationProceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021
EditorsXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages8
ISBN (Print)9789811617805
Publication statusPublished - 2022
Event6th International Congress on Information and Communication Technology, ICICT 2021 - Virtual, Online
Duration: 2021 Feb 252021 Feb 26

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


Conference6th International Congress on Information and Communication Technology, ICICT 2021
CityVirtual, Online

Bibliographical note

Funding Information:
Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Republic of Korea government (MSIT) (No. NRF– 2020R1A2C1005918). This research was supported by the MOTIE (Ministry of Trade, Industry, and Energy) in Korea, under the Fostering Global Talents for Innovative Growth Program (P0008749) supervised by the Korea Institute for Advancement of Technology (KIAT).

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.


  • Classification
  • Feature extraction
  • Patent big data analysis
  • Patent litigation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications


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