Query Classification with Sparse Soft Labels

Data is received characterizing a plurality of search queries including user provided natural language representations of the plurality of search queries of an item catalogue and first labels associated with the plurality of search queries. Label weights characterizing a frequency of occurrence of the first labels within the received data is determined using the received data. Second labels are determined. The determining of the second labels includes removing or changing the first labels from the received data to reduce a total number of allowed labels for at least one search query. A classifier is trained using the plurality of search queries, the second labels, and the determined weights. The classifier is trained to predict, from an input search query, a prediction weight and at least one prediction label associated with the prediction weight. Related apparatus, systems, techniques, and articles are also described.