@inproceedings{sweed-etal-2025-finding,
    title = "Finding your {MUSE}: Mining Unexpected Solutions Engine",
    author = "Sweed, Nir  and
      Hakim, Hanit  and
      Wolfson, Ben  and
      Lifshitz, Hila  and
      Shahaf, Dafna",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.emnlp-main.1547/",
    doi = "10.18653/v1/2025.emnlp-main.1547",
    pages = "30407--30422",
    ISBN = "979-8-89176-332-6",
    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. We introduced MUSE, a novel engine to find unexpected solutions to problems. This engine consists of the inspiration graph, whose problem and solution nodes were extracted from 500K patent descriptions. For a given problem, MUSE aims to enhance users' creative problem solving by providing them with inspirations sampled from the inspiration graph. A user study indicates that participants exposed to MUSE{'}s inspirations generated more creative ideas, both in terms of absolute number (up to 19{\%} increase over participants not given inspirations) and ratio (75{\%}, compared to 49{\%} for no inspirations)."
}