Exploring for Inspiration: A Bayesian Inference Based Approach to Design By Analogy Retrieval

人们在日常生活中使用类比推理，通过将熟悉的事物与之类比来理解新事物。工程设计人员在称为类比设计（DbA）的方法中使用了相同的原则。许多突破性的创新都是通过DbA出现的，包括自清洁、受莲花启发的户外表面涂料，以及受早期葡萄酒压榨机启发的第一台印刷机。尽管类似的灵感可以偶然得到，但DbA的正式方法可以使该方法得到更广泛、更可靠的应用。迄今为止，大多数类比识别技术都依赖于基于查询的方法，例如关键字搜索。相反，这项研究将使可视化技术能够探索工程设计创新的类比，并显示这种可视化方法优于基于查询的DbA。研究结果将通过提高工程师以一种比现有技术更具活力和探索性的方式寻找类比灵感的能力，推进工程设计和促进工程创新。研究结果将以开放源代码的形式提供给许多领域的研究人员使用、比较和整合。拓展工作将把工程设计和DbA的研究理念融入到机械工程女童子军徽章中。本研究的目的是验证基于探索的方法比基于查询的方法更有效地检索DbA实践中的刺激的假设。通过使用主题建模技术、来自美国专利数据库的大数据和可视化分析技术，该研究将改变DbA灵感的发现方式。这些结果将为设计师探索设计空间提供更直观、动态的访问和可操作性。从DbA的文献和理论中推导出类比信息和外部刺激的性质。使用潜在语义分析、潜在狄利克雷分配、非负矩阵分解、数据可视化技术和人机交互设计原则，构建可视化的、可探索的、可操作的设计库；将对存储库进行比较，以确定哪个存储库最能支持DbA的检索阶段。将开发和测试新颖的、种子的、分层的主题建模方法。这些DbA属性和技术将通过设计过程的认知研究进行测试。通过在比以前更大的存储库规模上支持探索性方法，可以在创新的道路上实现转换效果。这项研究将使复杂设备设计的工程，导致产品具有更高的性能，更好的材料使用，更少的资源消耗。

People use analogical reasoning in everyday life to understand new things by drawing parallels with familiar things. The same principle is used by engineering designers in an approach called Design by Analogy (DbA). Many groundbreaking innovations have emerged through DbA, including self-cleaning, outdoor-surface paint that was inspired by the lotus flower and the first printing press, which was inspired by the early wine press. Although analogical inspiration can be arrived at serendipitously, formal approaches for DbA enable reliable the approach to be applied more widely and reliably. To date, most analogy identification techniques have relied on a query-based approaches, such as key-word search. Instead, this research will enable visual techniques for exploring analogies for engineering design innovation and show the superiority of this visual approach over a query-based DbA. The results will advance engineering design and promote engineering innovations by enhancing the ability of engineers to search for analogical inspiration in a way that is more dynamic and exploratory than current techniques. Results will be made available in an open-source format for use, comparison, and integration by researchers across many fields. Outreach efforts will incorporate research ideas about engineering design and DbA into a mechanical engineering Girl Scout badge. The objective of this research is to test the hypothesis that exploration-based approaches are more effective than query-based approaches for retrieval of stimuli for DbA practices. By using Topic Modeling techniques, big data from the US patent database, and visual analytics techniques, the research will transform the way DbA inspiration is found. The results will give designers more intuitive, dynamic access and maneuverability for exploring the design space. Properties of analogical information and external stimuli will be extracted deductively from literature and theory of DbA. Visual, exploration-enabling, manipulable design repositories will be constructed using Latent Semantic Analysis, Latent Dirichlet Allocation, Non-negative Matrix Factorization, techniques in data visualization and Human Computer Interaction design principles; the repositories will be compared to identify which can best support the retrieval stage of DbA. Novel, seeded, hierarchical topic modeling methods will be developed and tested. These DbA properties and techniques will be tested with cognitive studies of the design process. By supporting an exploratory approach at a larger scale of repository size than ever before, transformational effects can be achieved on the path to innovation. This research will enable engineering of complex device designs that lead to products with improved performance, better material use, and fewer resources consumed.