An interpretable latent variable model for attribute applicability in the Amazon catalogue

30 Nov 2017Tammo RukatDustin LangeCédric Archambeau

Learning attribute applicability of products in the Amazon catalog (e.g., predicting that a shoe should have a value for size, but not for battery-type at scale is a challenge. The need for an interpretable model is contingent on (1) the lack of ground truth training data, (2) the need to utilise prior information about the underlying latent space and (3) the ability to understand the quality of predictions on new, unseen data... (read more)

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