Understand
We introduce an unsupervised approach to efficiently discover the underlying features in a data set via crowdsourcing.
- Our queries ask crowd members to articulate a feature common to two out of three displayed examples.
- In addition we also ask the crowd to provide binary labels to the remaining examples based on the discovered features.
- The triples are chosen adaptively based on the labels of the previously discovered features on the data set.
Built on
Features of similarity
Amos Tversky · 1977
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Honglak Lee, Alexis Battle, Rajat Raina, and Andrew Y Ng · 2006
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Ali Farhadi, Ian Endres, Derek Hoiem, and David Forsyth · 2009
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Then
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