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International Conference on - Design Computing and Cognition

DCC 2018: Design Computing and Cognition '18 pp 195–212Cite as

Exploring the Feature Space to Aid Learning in Design Space Exploration

Abstract

In this paper, we introduce the concept of exploring the feature space to aid learning in the context of design space exploration. The feature space is defined as a possible set of features mapped in a 2D plane with each axis representing different interestingness measures, such as precision or recall. Similar to how a designer explores the design space, one can explore the feature space by observing how different features vary in their ability to explain a set of design solutions. We hypothesize that such process helps designers gain a better understanding of the design space. To test this hypothesis, we conduct a controlled experiment with human subjects. The result suggests that exploring the feature space has the potential to enhance the user’s ability to identify important features and predict the performance of a design. However, such observation is limited only to the participants with some previous experience with design space exploration.

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Authors and Affiliations

  1. Cornell University, Ithaca, NY, USA

    Hyunseung Bang, Yuan Ling Zi Shi, Guy Hoffman, So-Yeon Yoon & Daniel Selva

Authors
  1. Hyunseung Bang
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  2. Yuan Ling Zi Shi
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  3. Guy Hoffman
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  4. So-Yeon Yoon
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  5. Daniel Selva
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Corresponding author

Correspondence to Hyunseung Bang .

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Editors and Affiliations

  1. Department of Computer Science and School of Architecture, University of North Carolina at Charlotte, Charlotte, NC, USA

    Prof. John S. Gero

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Bang, H., Shi, Y.L.Z., Hoffman, G., Yoon, SY., Selva, D. (2019). Exploring the Feature Space to Aid Learning in Design Space Exploration. In: Gero, J. (eds) Design Computing and Cognition '18. DCC 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-05363-5_11

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  • DOI: https://doi.org/10.1007/978-3-030-05363-5_11

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