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Real-time bidding and advertising content generation

  • US 10,192,238 B2
  • Filed: 12/21/2012
  • Issued: 01/29/2019
  • Est. Priority Date: 12/21/2012
  • Status: Active Grant
First Claim
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1. A method of generating a personalized Internet advertisement, the method comprising:

  • receiving, by one or more server computing devices and in real-time, user information associated with a user of a client computing device;

    deriving one or more user features from the user information associated with the user, the one or more user features comprising one or more user intents;

    generating, by the one or more server computing devices, one or more intent graphs relative to the user and an advertiser having a plurality of advertiser intents;

    matching, by the one or more server computing devices, using the one or more intent graphs, the one or more user intents with one or more of the plurality of advertiser intents associated with products or services offered by the advertiser, wherein matching the one or more user intents with the one or more of the plurality of advertiser intents comprises;

    accepting, at an intent matcher processing subsystem of the one or more server computing devices, one or more intent match context objects, wherein the one or more intent match context objects comprise a list of topic-term pairs as output, each of the one or more intent match context objects are associated with at least one of the one or more user intents, the one or more intent match context objects are accepted as input and returned as output at each of a plurality of processing subsystems of a processing pipeline of the one or more server computing devices implementing an intent match runtime system, the plurality of processing subsystems comprising the intent matcher processing subsystem, and each respective processing subsystem of the plurality of processing subsystems is configured to change only a context field of a context object of the one or more intent match context objects corresponding to a responsibility of the each respective processing subsystem;

    computing, by the one or more server computing devices, and using one or more statistical models, a similarity score between the one or more user features and the one or more of the plurality of advertiser intents;

    determining, by the one or more server computing devices, that the user information is accepted, including determining that the similarity score exceeds a threshold; and

    in response to accepting the user information, generating, by the one or more server computing devices, the personalized Internet advertisement based on the matching of the one or more user intents and the one or more of the plurality of advertiser intents.

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