用专利数据构建功能图谱，挖掘创新灵感。
Finding your MUSE: Mining Unexpected Solutions Engine
- 构建功能概念图谱，显式表达抽象关系
- 基于50万份专利生成大规模高质量图谱
- 适合创新研究与跨领域设计启发
创新者常受限于现有方案或初步想法，难以探索新解。本文提出构建功能概念图谱（FCGs）的方法，通过连接功能元素实现抽象、问题重构与类比启发。该方法生成的大规模、高质量图谱明确表达了抽象关系，克服了以往工作的局限。我们进一步提出MUSE算法，利用FCGs为具体问题生成创造性灵感。通过在50万份专利上计算得到的FCG，我们将其公开以支持后续研究。
原文摘要 · Abstract (English)
Innovators often exhibit cognitive fixation on existing solutions or nascent ideas, hindering the exploration of novel alternatives. This paper introduces a methodology for constructing Functional Concept Graphs (FCGs), interconnected representations of functional elements that support abstraction, problem reframing, and analogical inspiration. Our approach yields large-scale, high-quality FCGs with explicit abstraction relations, overcoming limitations of prior work. We further present MUSE, an algorithm leveraging FCGs to generate creative inspirations for a given problem. We demonstrate our method by computing an FCG on 500K patents, which we release for further research.
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