The Journal of Intellectual Property (J Intellect Property; JIP)

KCI Indexed
OPEN ACCESS, PEER REVIEWED

pISSN 1975-5945
eISSN 2733-8487

Large Language Model-based R&D Solution Analysis Approach Using Problem-Solution Information of Patents

CONTENTS

Research article

Citation: Lee S, et al. 2024. Large Language Model-based R&D Solution Analysis App ro ac h Us in g Pr obl em- Sol n Information of Patents. The Journal of Intellectual Property 19(3), 155-180.

DOI: https://doi.org/10.34122/jip.2024.19.3.8

The Journal of Intellectual Property, 2024 September, 19(3): 155-180. 

Received on 2 July 2024, Revised on 6 August 2024, Accepted on 3 September 2024, Published on 30 September 2024.

Large Language Model-based R&D Solution Analysis Approach Using Problem-Solution Information of Patents

Seunghyun Lee1, Jiho Lee2, Seoin Park3, Jae-Min Lee4, Hong-Woo Chun5, Janghyeok Yoon6*

1PhD Candidate, Department of Industrial Engineering, Konkuk University, Republic of Korea
2Director, AI Lab, Neopons Inc., Republic of Korea
3Master’s Student, Department of Industrial Engineering, Konkuk University, Republic of Korea
4Principal Researcher, Future Technology Analysis Center, Korea Institute of Science and Technology Information, Republic of Korea
5Director, Future Technology Analysis Center, Korea Institute of Science and Technology Information, Republic of Korea
6Professor, Department of Industrial Engineering, Konkuk University, Republic of Korea

*Corresponding Author: Janghyeok Yoon (janghyoon@konkuk.ac.kr)

Abstract

Patents, i.e., the output of research and development (R&D) activities, are regarded as a concentration of Problem–Solution information. Despite various patent analysis studies aimed at solving problems, large language model (LLM)-based studies are scarce. LLMs, which are effective for natural language processing tasks, such as text summarization and generation, have been applied in numerous fields, including healthcare, finance, and law. By learning the Problem-Solution information of patents as an LLM instead of merely examining existing R&D solutions, one can generate new solutions applicable to a specified problem. Therefore, this study proposes an approach to generate and analyze new R&D solutions using LLMs. Our systematic approach involves 1) collecting numerous patents and constructing a database; 2) extracting Problem-Solution information from the Common Application Form section of patents and constructing a Problem-Solution dataset; 3) fine-tuning an LLM using the problem-solution dataset and generating R&D solutions; and 4) analyzing R&D solutions to present a technology concept portfolio map. This study extends beyond the existing R&D solution exploration, presents a new approach for generating solutions, and suggests technology concepts using LLMs. Therefore, this study contributes to the expansion of the available options and fosters innovation in R&D field.

Keywords

Patent analysis, Problem-Solution information, R&D solution, Large language model, Fine-tuning

Funding

The author received manuscript fees for this article from Korea Institute of Intellectual Property.

Conflicts of interest

No potential conflict of interest relevant to this article was reported.