Finding analogical inspirations in distant domains is a powerful way of solving problems. However, as the number of inspirations that could be matched and the dimensions on which that matching could occur grow, it becomes challenging for designers to find inspirations relevant to their needs. Furthermore, designers are often interested in exploring specific aspects of a product-- for example, one designer might be interested in improving the brewing capability of an outdoor coffee maker, while another might wish to optimize for portability. In this paper we introduce a novel system for targeting analogical search for specific needs. Specifically, we contribute a novel analogical search engine for expressing and abstracting specific design needs that returns more distant yet relevant inspirations than alternate approaches.
@article{arxiv.1712.06880,
title = {Analogy Mining for Specific Design Needs},
author = {Karni Gilon and Felicia Y Ng and Joel Chan and Hila Lifshitz Assaf and Aniket Kittur and Dafna Shahaf},
journal= {arXiv preprint arXiv:1712.06880},
year = {2017}
}