知識の流れは科学からAI技術へ: 核と仲介の技術的役割を特定する
Seokhui Lee1, Jisoo Hur2, Junseok Hwang1
1Technology Management, Economics and Policy Program, College of Engineering/ Integrated Major in Smart City Global Convergence, Seoul National University, Seoul, Republic of Korea.
PloS one
|February 19, 2026
まとめ
この研究は,人工知能 (AI) の科学から技術への知識の流れを地図化しています. 私たちはAIの特許を分析し,主要なトレンドとイノベーションの経路を明らかにし,研究開発と政策の洞察を提供しました.
科学分野:
- 人工知能 (AI) について
- イノベーション研究 イノベーション研究
- ビビロメトリクス (Bibliometrics) とは
背景:
- 人工知能 (AI) は急速に進歩し,産業全体に統合されています.
- 科学的研究からAI技術開発への知識の流れは極めて重要ですが,十分に研究されていません.
- 現存する研究では,AIの科学から技術への知識経路の体系的な分析が欠けている.
研究 の 目的:
- AIの進化を支える科学から技術への知識の流れを体系的に調査する.
- 人工知能に関連する知識の移転を探求するための意味論的枠組みを提案し,適用する.
- AI開発における重要な技術的動向と構造的経路を特定する.
主な方法:
- 技術の分類と意味論的なトピック探査の2段階の枠組みを開発しました.
- CPCの共同発生ネットワークからの中心性の測定を用いた機密化されたAI特許.
- 特許と科学出版の摘要にBERTopicモデリングを適用し,トピックのラベリングに生成AIを使用しました.
主要な成果:
- 2002年から2021年の間に提出されたAI特許を分析した.
- 重要な技術的トレンドを追跡し,知識の流れの構造的経路を特定しました.
- 科学的発見とAIのイノベーションの間のダイナミックな相互作用を明らかにした.
結論:
- この発見は,科学的な知識によって推進されるAIの技術的進化の構造的な理解を提供します.
- 企業の研究開発 (R&D) 戦略に対する実用的な意味合いを提供します.
- 急速に進化するAIの景観のためのイノベーション政策の設計を伝える.
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