BERTopic을 활용한 텍스트마이닝 기반 인공지능 반도체 기술 및 연구동향 분석
Topic Modeling on Patent and Article Big Data Using BERTopic and Analyzing Technological Trends of AI Semiconductor Industry
김현경(KT); 이정훈(Graduate School of Information, Yonsei University); 강선구(IoT Service Convergence Graduate School of Information, Yonsei University)
31권 1호, 139~161쪽
초록
The Fourth Industrial Revolution has spurred widespread adoption of AI-based services, driving global interest in AI semiconductors for efficient large-scale computation. Text mining research, historically using LDA, has evolved with machine learning integration, exemplified by the 2021 BERTopic technology. This study employs BERTopic to analyze AI semiconductor-related patents and research data, generating 48 topics from 2,256 patents and 40 topics from 1,112 publications. While providing valuable insights into technology trends, the study acknowledges limitations in taking a macro approach to the entire AI semiconductor industry. Future research may explore specific technologies for more nuanced insights as the industry matures.
Abstract
The Fourth Industrial Revolution has spurred widespread adoption of AI-based services, driving global interest in AI semiconductors for efficient large-scale computation. Text mining research, historically using LDA, has evolved with machine learning integration, exemplified by the 2021 BERTopic technology. This study employs BERTopic to analyze AI semiconductor-related patents and research data, generating 48 topics from 2,256 patents and 40 topics from 1,112 publications. While providing valuable insights into technology trends, the study acknowledges limitations in taking a macro approach to the entire AI semiconductor industry. Future research may explore specific technologies for more nuanced insights as the industry matures.
- 발행기관:
- 한국데이터전략학회
- 분류:
- 경영학