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

doi:10.1007/978-981-16-1781-2_76

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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 language	English
Title of host publication	Proceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021
Editors	Xin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	877-884
Number of pages	8
ISBN (Print)	9789811617805
DOIs	https://doi.org/10.1007/978-981-16-1781-2_76
Publication status	Published - 2022
Event	6th International Congress on Information and Communication Technology, ICICT 2021 - Virtual, Online Duration: 2021 Feb 25 → 2021 Feb 26

Publication series

Name	Lecture Notes in Networks and Systems
Volume	216
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	6th International Congress on Information and Communication Technology, ICICT 2021
City	Virtual, Online
Period	21/2/25 → 21/2/26

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.

Keywords

Classification
Feature extraction
Patent big data analysis
Patent litigation

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-981-16-1781-2_76

Cite this

Kim, Y., Lee, J., Kang, J., Lee, J., Jang, D., & Park, S. (2022). A Study on the Comparison of Feature Extraction Methods for Classification of Patent Litigation. In X.-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), Proceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021 (pp. 877-884). (Lecture Notes in Networks and Systems; Vol. 216). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-1781-2_76

A Study on the Comparison of Feature Extraction Methods for Classification of Patent Litigation. / Kim, Youngho; Lee, Junseok; Kang, Jiho et al.
Proceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021. ed. / Xin-She Yang; Simon Sherratt; Nilanjan Dey; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2022. p. 877-884 (Lecture Notes in Networks and Systems; Vol. 216).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, Y, Lee, J, Kang, J, Lee, J, Jang, D & Park, S 2022, A Study on the Comparison of Feature Extraction Methods for Classification of Patent Litigation. in X-S Yang, S Sherratt, N Dey & A Joshi (eds), Proceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021. Lecture Notes in Networks and Systems, vol. 216, Springer Science and Business Media Deutschland GmbH, pp. 877-884, 6th International Congress on Information and Communication Technology, ICICT 2021, Virtual, Online, 21/2/25. https://doi.org/10.1007/978-981-16-1781-2_76

Kim Y, Lee J, Kang J, Lee J, Jang D, Park S. A Study on the Comparison of Feature Extraction Methods for Classification of Patent Litigation. In Yang XS, Sherratt S, Dey N, Joshi A, editors, Proceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 877-884. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-16-1781-2_76

Kim, Youngho ; Lee, Junseok ; Kang, Jiho et al. / A Study on the Comparison of Feature Extraction Methods for Classification of Patent Litigation. Proceedings of Sixth International Congress on Information and Communication Technology - ICICT 2021. editor / Xin-She Yang ; Simon Sherratt ; Nilanjan Dey ; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2022. pp. 877-884 (Lecture Notes in Networks and Systems).

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abstract = "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.",

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

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