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

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Proceedings of Sixth International Congress on Information and Communication Technology

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 216))

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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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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).

Author information

Authors and Affiliations

  1. Department of Industrial Management Engineering, Korea University, Seoul, Republic of Korea

    Youngho Kim, Juhyun Lee & Dongsik Jang

  2. MICube Solution, Seoul, Republic of Korea

    Junseok Lee

  3. Machine Learning Big Data Institute, Korea University, Seoul, Republic of Korea

    Jiho Kang

  4. Department of Big Data Statistics, CheongJu University, Cheong Ju, Republic of Korea

    Sangsung Park

Authors
  1. Youngho Kim
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  2. Junseok Lee
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  3. Jiho Kang
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  4. Juhyun Lee
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  5. Dongsik Jang
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  6. Sangsung Park
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Corresponding author

Correspondence to Youngho Kim .

Editor information

Editors and Affiliations

  1. Middlesex University, London, UK

    Xin-She Yang

  2. The University of Reading, Reading, UK

    Simon Sherratt

  3. JIS University, Kolkata, India

    Nilanjan Dey

  4. Global Knowledge Research Foundation, Ahmedabad, India

    Amit Joshi

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

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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: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Sixth International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 216. Springer, Singapore. https://doi.org/10.1007/978-981-16-1781-2_76

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