A posteriori novelty metrics are often used in design research, in order to extract important information about creativity. However, different assessment approaches can be found in the literature, each of them with related pros and cons. In particular, weighted uncommonness, overall uncommonness and uncommonness across groups are the three main families of a-posteriori novelty metrics identified in this paper. Each of the considered literature metrics can provide specific types of information about the uncommonness of ideas, but in certain experimental circumstances, it could be difficult to rapidly identify the best-suited approach. This paper proposes an integrated procedure where the advantages offered by the three families of metrics can be applied concurrently. A generic case study is used for a first application of the proposal, and the obtained results show that a more comprehensive set of information about a-posteriori novelty can be extracted. In particular, novelty data from the three families of metrics are extracted in a single assessment process.
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