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arXiv · 2509.05072

Finding your MUSE: Mining Unexpected Solutions Engine

Nir Sweed·Hanit Hakim·Ben Wolfson·Hila Lifshitz·Dafna Shahaf
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Abstract

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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Nir Sweed, Hanit Hakim, Ben Wolfson, Hila Lifshitz, Dafna Shahaf. 2025-09-05. Finding your MUSE: Mining Unexpected Solutions Engine. https://arxiv.org/abs/2509.05072

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