Analogy mining for specific design needs

Karni Gilon, Joel Chan, Felicia Y. Ng, Hila Lifshitz-Assaf, Aniket Kittur, Dafna Shahaf

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

32 Scopus citations

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.

Original languageAmerican English
Title of host publicationCHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationEngage with CHI
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450356206, 9781450356213
DOIs
StatePublished - 20 Apr 2018
Event2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 - Montreal, Canada
Duration: 21 Apr 201826 Apr 2018

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
Volume2018-April

Conference

Conference2018 CHI Conference on Human Factors in Computing Systems, CHI 2018
Country/TerritoryCanada
CityMontreal
Period21/04/1826/04/18

Bibliographical note

Publisher Copyright:
© 2018 ACM.

Keywords

  • Abstraction
  • Computational analogy
  • Creativity
  • Focus
  • Innovation
  • Inspiration
  • Product dimensions
  • Text embedding

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