Abstract: A data processing system implements obtaining query parameters for a query for content items in a datastore, the query parameters including attributes of content items for which a search is to be conducted; obtaining a first set of content items from a content datastore based on the query parameters; analyzing the first set of content items using a first machine learning model trained to generate relevant content information that identifies a plurality of relevant content items included in the first set of content items; and analyzing the plurality of relevant content items using a second machine learning model configured to output novel content information, the novel content information including a plurality of content items predicted to be relevant and novel, the novel content information ranking the plurality of content items predicted to be relevant and novel based on a novelty score associated with each respective content item.

Abstract: A data processing system implements obtaining query parameters for a query for content items in a datastore, the query parameters including attributes of content items for which a search is to be conducted; obtaining a first set of content items from a content datastore based on the query parameters; analyzing the first set of content items using a first machine learning model trained to generate relevant content information that identifies a plurality of relevant content items included in the first set of content items; and analyzing the plurality of relevant content items using a second machine learning model configured to output novel content information, the novel content information including a plurality of content items predicted to be relevant and novel, the novel content information ranking the plurality of content items predicted to be relevant and novel based on a novelty score associated with each respective content item.

Abstract: A computer implemented method includes receiving an image that includes a type of object, segmenting the object into multiple segments via a trained segmentation machine learning model, and inputting the segments into multiple different attribute extraction models to extract different types of attributes from each of the multiple segments.