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In the digital era, enterprises must proactively identify technological opportunities to maintain a competitive edge. This study presents an AI-powered methodology to identify technological opportunities by integrating user demands with cross-domain patent analysis. The framework constructs a three-layer knowledge graph (demand-core, tech-related, domains) through: (1) Demand extraction from e-commerce reviews and patent categorization using IPC codes; (2) SAO structure enhancement via Language Technology Platform (LTP) for semantic alignment; (3) Opportunity identification using graph clustering and purity metrics between demand-technology layers; (4) Feasibility validation through cross-domain purity evaluation. Validated via an insulin pump case study, this approach effectively bridges user needs and technological convergence, enabling enterprises to systematically discover actionable innovation pathways.

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Research on Opportunities Identification and Implementation Methods Based on Multi-layer Knowledge Graphs

  • 会议论文

  • 发表日期：

    2026年

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  • Jianguang Sun,
  • Delong Zhang,
  • Xiangjie Lin,
  • Yongsheng Zhai

摘要

In the digital era, enterprises must proactively identify technological opportunities to maintain a competitive edge. This study presents an AI-powered methodology to identify technological opportunities by integrating user demands with cross-domain patent analysis. The framework constructs a three-layer knowledge graph (demand-core, tech-related, domains) through: (1) Demand extraction from e-commerce reviews and patent categorization using IPC codes; (2) SAO structure enhancement via Language Technology Platform (LTP) for semantic alignment; (3) Opportunity identification using graph clustering and purity metrics between demand-technology layers; (4) Feasibility validation through cross-domain purity evaluation. Validated via an insulin pump case study, this approach effectively bridges user needs and technological convergence, enabling enterprises to systematically discover actionable innovation pathways.