Generalized linear mixed model with destination personalization

A system comprising:

• at least one hardware processor;
• and
• a non-transitory machine-readable medium embodying a set of instructions that, when executed by the at least one hardware processor, cause the at least one processor to perform operations, the operations comprising:
• for each one of the plurality of destination user candidates, generating a corresponding score based on a generalized linear mixed model comprising a global model and a destination user model, the global model being a generalized linear model based on feature data of a profile of a source user and feature data of a profile of the one of the plurality of destination user candidates, and the destination user model being a random effects model based on behavior data of the one of the plurality of destination user candidates indicating whether the one of the plurality of destination user candidates performed a particular destination user action in response to a particular source user action performed by reference source users determined to have profiles with feature data similar to the feature data of the profile of the source user, the particular source user action being directed towards the one of the plurality of destination user candidates;
• selecting a subset of the plurality of destination user candidates from the plurality of destination user candidates based on the corresponding scores of the subset of the plurality of destination user candidates;
• and
• causing a recommendation to be displayed on a computing device of the source user, the recommendation comprising a recommendation to perform the particular source user action for the selected subset of destination user candidates.

A non-transitory machine-readable medium embodying a set of instructions that, when executed by at least one hardware processor, cause the processor to perform operations, the operations comprising:

• for each one of the plurality of destination user candidates, generating a corresponding score based on a generalized linear mixed model comprising a global model and a destination user model, the global model being a generalized linear model based on feature data of a profile of a source user and feature data of a profile of the one of the plurality of destination user candidates, and the destination user model being a random effects model based on behavior data of the one of the plurality of destination user candidates indicating whether the one of the plurality of destination user candidates performed a particular destination user action in response to a particular source user action performed by reference source users determined to have profiles with feature data similar to the feature data of the profile of the source user, the particular source user action being directed towards the one of the plurality of destination user candidates;
• selecting a subset of the plurality of destination user candidates from the plurality of destination user candidates based on the corresponding scores of the subset of the plurality of destination user candidates;
• and
• causing a recommendation to be displayed on a computing device of the source user, the recommendation comprising a recommendation to perform the particular source user action for the selected subset of destination user candidates.