Yahoo Assets LLC

Yahoo Ad Tech LLC

Gaurav Srivastava

Maxim I Sviridenko

Benjamin Jackson Culpepper

Shaunak Mishra

Eric McVoy Dodds

Mikhail Kuznetsov

One or more systems and/or methods for combining vectors output by multiple different mechanisms for content item retrieval are provided. An image encoder may output a first set of vectors generated by an image model using an input image as input. A text encoder may output a second set of vectors generated by a text model using input text as input. A vector combination module may combine the first set of vectors and the second set of vectors to create a vector output. A weight is applied to the vector output to create a weighted output. An output vector is generated based upon a combination of the first set of vectors, the second set of vectors, and the weighted output. The output vector is used to query a catalog to identify a content item related to the input image and the input text.

Combining vectors output by multiple different mechanisms for content item retrieval

In an example, a first set of text may be received from a client device. A set of content items may be selected from among content items based upon the first set of text and a plurality of sets of content item text associated with the content items. A set of terms may be determined based upon the first set of text and the set of content items. A similarity profile associated with the set of terms may be generated. The similarity profile is indicative of similarity scores associated with similarities between terms of the set of terms. Relevance scores associated with the set of terms may be determined based upon the similarity profile. One or more search terms may be selected from among the set of terms based upon the relevance scores. A search may be performed based upon the one or more search terms.

Search query generation based upon received text

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San Francisco, CA, United States of America

Gaurav Srivastava