Identification of synthetic examples for improving search rankings

Abstract

Methods, systems, and machine-readable media for identifying synthetic media file examples to train a supervised machine learned ranking algorithm to rank relevance of media files to a search query are provided. In one aspect, a method includes identifying a search query for a search engine for a collection of media files from previously received search queries, and selecting at least one training media file from the collection as a synthetic negative example for the search query. The method also includes providing a training set to a supervised machine learned ranking algorithm. The training set includes an identification of the search query, a copy of the training media file, and a first indicator that the training media file is a synthetic negative example for the search query. The method further includes providing, to the algorithm, the search query and the collection, and receiving, from the algorithm, a ranking of the collection.