Working with multiple alternatives is a central activity in design; therefore, we expect computational systems to support such work. There is a need to find out the tool features supporting this central activity so that we can build new systems. To explore such features, we propose a method that aims to enable interaction with a large number of design alternatives by similarity-based exploration. Using existing data analysis and visualization techniques adopting similarity-based search, we formalized the method and its elements by focusing on systematic filtering, clustering, and choosing alternatives. We present a scenario on developing conceptual designs for a residential apartment to illustrate how the method can be applied, as well as to reveal the limitation of current tools and the potential interactive clustering and filtering features for the new systems coupled with parametric design.
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