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Predictive analysis of target behaviors utilizing RNN-based user embeddings

  • US 10,558,852 B2
  • Filed: 11/16/2017
  • Issued: 02/11/2020
  • Est. Priority Date: 11/16/2017
  • Status: Active Grant
First Claim
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1. A computer-implemented method for generating next-user-action predictive models using navigation sequences, the method comprising:

  • obtaining a set of navigation sequences associated with a set of users, each navigation sequence in the set of navigation sequences including a set of user actions sequentially performed during a navigation session, and each navigation sequence being associated with a user included in the set of users;

    applying a Recurrent Neural Network (RNN) to the set of navigation sequences to encode each navigation sequence in the set of navigation sequences into a user embedding that reflects a temporally-defined navigation pattern for the associated user; and

    applying a classifier to the user embeddings to create a next-user-action predictive model for predicting next-actions of users.

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