A Study on the Development of LDA Algorithm-Based Financial Technology Roadmap Using Patent Data

• 발행기관: 한국인공지능학회
• 저자명: Koopo KWON Kyounghak LEE
• 간행물 정보: 『인공지능연구』Vol.12 No. 3, 17~24쪽, 전체 8쪽
• 주제분류: 복합학 > 과학기술학
• 파일형태: PDF
• 발행일자: 2024.09.30

국문 초록

This study aims to derive a technology development roadmap in related fields by utilizing patent documents of financial technology. To this end, patent documents are extracted by dragging technical keywords from prior research and related reports on financial technology. By applying the TF-IDF (Term Frequency-Inverse Document Frequency) technique in the extracted patent document, which is a text mining technique, to the extracted patent documents, the Latent Dirichlet Allocation (LDA) algorithm was applied to identify the keywords and identify the topics of the core technologies of financial technology. Based on the proportion of topics by year, which is the result of LDA, promising technology fields and convergence fields were identified through trend analysis and similarity analysis between topics. A first-stage technology development roadmap for technology field development and a second-stage technology development roadmap for convergence were derived through network analysis about the technology data-based integrated management system of the high-dimensional payment system using RF and intelligent cards, as well as the security processing methodology for data information and network payment, which are identified financial technology fields. The proposed method can serve as a sufficient reason basis for developing financial technology R&D strategies and technology roadmaps.

목차

1. Introduction

2. Theoretical Background

3. Research Methods and Materials

4. Results

5. Conclusions

References

키워드

Patent Analysis Financial Technology Clustering Techniques Trend Analysis Network Analysis Technology Development Roadmap LDA