Inspirational stimuli are known to be effective in supporting ideation during the design process. However, underexplored in past work are the processes and modalities used to search for inspirational stimuli. In the current work, we developed a multi-modal search platform that retrieves 3D model parts based on text, appearance, and function-based search inputs. This work presents the results of an experimental study (n=21) in which the search platform was used to find parts identified as potentially useful for inspiring solutions to a design challenge. Users could engage with three search modalities: search by keywords, by curated 3D parts, and by user-assembled 3D parts in their workspace. When searching by parts that are curated or in their workspace, additional control over the similarity of appearance and function of results to the input was available to users. The results of this study demonstrate that search modality affects how and how often users search, how users engage with retrieved search results, and how broadly the search space is covered. Specific findings suggest that methods supporting multi-modal search should enable the ability to iteratively modify search inputs, towards finding relevant examples. Moreover, to encourage a broader coverage of search results, randomly encountered examples should be provided to users to inspire new subsequent searches.

Multi-Modal Search for Inspirational Examples in Design

Paper Proceedings: https://asmedigitalcollection.asme.org/IDETC-CIE/IDETC-CIE2021/volume/85369

ASME 2021 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE2021)

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