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System and method for concurrently conducting cause-and-effect experiments on content effectiveness and adjusting content distribution to optimize business objectives

  • US 8,458,103 B2
  • Filed: 01/04/2010
  • Issued: 06/04/2013
  • Est. Priority Date: 01/07/2009
  • Status: Active Grant
First Claim
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1. A computer-implemented method, comprising:

  • conducting an experiment using experimental content to determine effectiveness of communication content; and

    executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric, wherein;

    the machine learning routine comprises a reinforcement learning routine, the reinforcement learning routine comprising one or both of an explore routine associated with explore content and an exploit routine associated with exploit content;

    the experiment is conducted in accordance with a schedule comprising a plurality of time-slot samples;

    for experimental content that are related to either of explore or exploit content, using a first plurality of the time-slot samples unused for conducting the experiment for the explore or exploit routine; and

    for experimental content that are unrelated to either of explore or exploit content, using at least some of the experimental content and either of explore or exploit content in the same time-slot sample of the plurality of time-slot samples.

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