Method, medium, and system for providing trait-focused recommendations of computer applications

A non-transitory computer readable medium having instructions tangibly stored thereon, wherein the instructions, when executed cause a system to:

• receive a first set of recommendations of potential computer applications of interest from a recommendations engine having a neural network input layer, at least one neural network hidden layer and a neural network output layer, wherein the recommendations engine includes a plurality of interconnected nodes divided among the layers, the first set of recommendations generated based on a set of input features characterizing an entity provided to the recommendations engine;
• identify a commonality among at least some recommendations of the first set of recommendations, the commonality defining a priority trait for the entity;
• associate the priority trait with at least one priority feature from the set of input features;
• generate a modification, the modification modifying at least one of:
• the set of input features at one or more input nodes of the plurality of interconnected nodes provided as input to the recommendations engine so as to emphasize those features associated with the priority feature, the one or more input nodes being neural network nodes of the neural network input layer, or
• at least one weight of one or more hidden nodes of the plurality of interconnected nodes in the recommendations engine to bias selection of the priority feature, the one or more hidden nodes being neural network nodes of the at least one neural network hidden layer;
• provide the modification to the recommendations engine to generate a second set of recommendations of potential computer applications of interest;
• and,
• transmit the second set of recommendations to a computing device for the entity for presentation thereon.

A computer system for dynamically generating recommendations of computer applications, the computer system comprising:

• a processor in communication with a storage, the processor configured to execute instructions stored on the storage to cause the system to:
• receive a first set of recommendations of potential computer applications of interest from a recommendations engine having a neural network input layer, at least one neural network hidden layer and a neural network output layer, wherein the recommendations engine includes a plurality of interconnected nodes divided among the layers, the first set of recommendations generated based on a set of input features characterizing an entity provided to the recommendations engine;
• identify a commonality among at least some recommendations of the first set of recommendations, the commonality defining a priority trait for the entity;
• associate the priority trait with at least one priority feature from the set of input features;
• generate a modification, the modification to modify at least one of:
• the set of input features at one or more input nodes of the plurality of interconnected nodes provided as input to the recommendations engine so as to emphasize those features associated with the priority feature, the one or more input nodes being neural network nodes of the neural network input layer, or
• at least one weight of one or more hidden nodes of the plurality of interconnected nodes in the recommendations engine to bias selection of the priority feature, the one or more hidden nodes being neural network nodes of the at least one neural network hidden layer;
• provide the modification to the recommendations engine to generate a second set of recommendations of potential computer applications of interest;
• and,
• transmit the second set of recommendations to a computing device for the entity for presentation thereon.