×

Customized predictors for user actions in an online system

  • US 9,317,812 B2
  • Filed: 11/30/2012
  • Issued: 04/19/2016
  • Est. Priority Date: 11/30/2012
  • Status: Expired due to Fees
First Claim
Patent Images

1. A computer-implemented method comprising:

  • receiving, by an online system, a plurality of requests for generating predictors, each request specifying a type of action performed by users of the online system, a category of users, and criteria for identifying a successful instance of the type of action;

    for each request associated with a type of action, generating, by the online system, a predictor for the type of action, the generating comprising;

    generating a training data set from a plurality of successful instances and failure instances of the type of action performed by online system users selected in response to belonging to the specified category of users;

    training one or more candidate predictors using the training data set, wherein each candidate predictor comprises a machine learned model;

    evaluating performance of each candidate predictor by executing each predictor on a test data set generated from an additional plurality of successful instances and failure instances of the type of action performed by online system users selected in response to belonging to the specified category of users; and

    selecting a predictor for the type of action by comparing the performance of the one or more candidate predictors; and

    returning a handle corresponding to the generated predictor to a requester of the selected predictor;

    periodically generating a new predictor by;

    comparing performance of the new predictor against performance of a previously generated predictor; and

    responsive to the performance of the new predictor exceeding the performance of the previously generated predictor, replacing the previously generated predictor with the new predictor; and

    reducing a rate of periodically generating the new predictor for the action type responsive to an improvement in the performance of the new predictor compared to the performance of the previously generated predictor being below a threshold value.

View all claims
  • 4 Assignments
Timeline View
Assignment View
    ×
    ×