Large repositories of products, patents and scientific papers offer an opportunity for building systems that scour millions of ideas and help users discover inspirations. However, idea descriptions are typically in the form of unstructured text, lacking key structure that is required for supporting creative innovation interactions. Prior work has explored idea representations that were either limited in expressivity, required significant manual effort from users, or dependent on curated knowledge bases with poor coverage. We explore a novel representation that automatically breaks up products into fine-grained functional aspects capturing the purposes and mechanisms of ideas, and use it to support important creative innovation interactions: functional search for ideas, and exploration of the design space around a focal problem by viewing related problem perspectives pooled from across many products. In user studies, our approach boosts the quality of creative search and inspirations, substantially outperforming strong baselines by 50-60%.
|Original language||American English|
|Title of host publication||CHI 2022|
|Subtitle of host publication||Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems|
|Publisher||Association for Computing Machinery|
|Number of pages||15|
|State||Published - 29 Apr 2022|
|Event||2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 - Virtual, Online, United States|
Duration: 30 Apr 2022 → 5 May 2022
|Name||Conference on Human Factors in Computing Systems - Proceedings|
|Conference||2022 CHI Conference on Human Factors in Computing Systems, CHI 2022|
|Period||30/04/22 → 5/05/22|
Bibliographical noteFunding Information:
This work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant no. 852686, SIAM), US National Science Foundation, US-Israel Binational Science Foundation (NSF-BSF) grant no. 2017741.
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