Title: Exploring key machine learning technologies and developments in photonics from the perspective of patent examiners

Authors: Shu-Hao Chang; Chin-Yuan Fan

Addresses: Science and Technology Policy Research and Information Center, National Applied Research Laboratories, 14F., No. 106, Section 2, Heping E. Rd., Da'an Dist., Taipei, 10636, Taiwan ' Science and Technology Policy Research and Information Center, National Applied Research Laboratories, 14F., No. 106, Section 2, Heping E. Rd., Da'an Dist., Taipei, 10636, Taiwan

Abstract: As smart applications mature, the application of machine learning technologies in photonics has become a prospective research area. Thus, the present study investigated various patents identified and cited by examiners, and a technology network model was employed to identify key technologies. Several major technologies were identified, namely those pertaining to electric digital data processing, graphical data reading, signalling and calling systems, vehicles, vehicle fittings, and vehicle parts. Various differences between the technologies cited by applicants and examiners were discovered. The technologies most frequently cited by applicants pertained to diagnoses, surgeries, and identification, whereas those most often cited by examiners pertained to electric digital data processing; notably, examiners used the technologies in this field to approve, reject, or limit the scope of patent rights. The results of the present study can serve as a reference for researching and improving resource allocation.

Keywords: machine learning; photonics; patent examiner; patent analysis; network analysis; examiner citations.

DOI: 10.1504/IJTPM.2024.143513

International Journal of Technology, Policy and Management, 2024 Vol.24 No.4, pp.343 - 357

Received: 03 Jul 2023
Accepted: 24 Dec 2023
Published online: 30 Dec 2024 *

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