| CPC H04L 51/02 (2013.01) [G06N 3/04 (2013.01); G06N 3/08 (2013.01)] | 20 Claims |

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2. A method for improving prediction model accuracy by training a prediction model for a specific content domain based on aggregated training data from disparate content domains, the method comprising:
obtaining vector representations of requests and solutions of (i) a first group of requests and solutions related to a first content domain and (ii) a second group of requests and solutions related to a second content domain, the second content domain being different from the first content domain;
supplementing the requests and solutions of the first group with at least a subset of the requests and solutions of the second group based on similarity criteria between (i) a first set of vector representations of requests and a first solution to the requests in the first group and (ii) a second set of vector representations of requests and a second solution to the requests in the second group to generate an aggregated group of requests and solutions;
providing the aggregated group of requests and solutions as training data to a first prediction model to cause the first prediction model to generate matching vector representations for requests within the aggregated group of requests and solutions;
providing a user input, obtained from a client device associated with a user, to the first prediction model to obtain a prediction of a solution for the user input; and
generating for display, the solution to the user on the client device.
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