@inproceedings{e6962eb6df14485db120e1d5e65cfb0b,
title = "Analogy mining for specific design needs",
abstract = "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 an analogical search engine for expressing and abstracting specific design needs that returns more distant yet relevant inspirations than alternate approaches.",
keywords = "Abstraction, Computational analogy, Creativity, Focus, Innovation, Inspiration, Product dimensions, Text embedding",
author = "Karni Gilon and Joel Chan and Ng, {Felicia Y.} and Hila Lifshitz-Assaf and Aniket Kittur and Dafna Shahaf",
note = "Publisher Copyright: {\textcopyright} 2018 ACM.; 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 ; Conference date: 21-04-2018 Through 26-04-2018",
year = "2018",
month = apr,
day = "20",
doi = "https://doi.org/10.1145/3173574.3173695",
language = "الإنجليزيّة",
series = "Conference on Human Factors in Computing Systems - Proceedings",
booktitle = "CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems",
}