Abstract: Systems, methods and computer readable medium are provided for generating recommendations of computer applications for entities including: receiving, at an input of a neural network model, a set of input features for characteristics of a set of entities; automatically selecting a middle layer of the model from amongst one or more hidden layers; determining values at the middle layer for entities corresponding to output values of the nodes of the middle layer; measuring similarity distances for a first entity as compared to other entities of the set of entities based on distance between the corresponding values at the middle layer; identifying a similar entity to the first entity based on the measured similarity distance for the first entity to the similar entity being the shortest of the measured similarity distances; and providing a recommendation for a computer application for the first entity based on the similar entity.

Abstract: Systems, methods and computer readable medium are provided for generating recommendations of computer applications for entities including: receiving, at an input of a neural network model, a set of input features for characteristics of a set of entities; automatically selecting a middle layer of the model from amongst one or more hidden layers; determining values at the middle layer for entities corresponding to output values of the nodes of the middle layer; measuring similarity distances for a first entity as compared to other entities of the set of entities based on distance between the corresponding values at the middle layer; identifying a similar entity to the first entity based on the measured similarity distance for the first entity to the similar entity being the shortest of the measured similarity distances; and providing a recommendation for a computer application for the first entity based on the similar entity.

Abstract: Systems, methods and computer readable medium are provided for receiving a first set of recommendations of computer applications from a recommendations engine having an input layer, at least one hidden layer and an output layer, the recommendations generated based on a set of input features characterizing an entity; identifying a commonality among at least some recommendations for defining a priority trait for the entity; associating the priority trait with at least one priority feature from the set of input features; generating a modification for modifying at least one of: the set of input features provided as input to the recommendations engine to emphasize those features associated with the priority feature, or at least one weight of the hidden layer in the recommendations engine to bias selection of the priority feature; providing the modification to the recommendations engine to generate a second set of recommendations for display on a computing device.

Abstract: Systems, methods and computer readable medium are provided for generating recommendations of computer applications for entities including: receiving, at an input of a neural network model, a set of input features for characteristics of a set of entities; automatically selecting a middle layer of the model from amongst one or more hidden layers; determining values at the middle layer for entities corresponding to output values of the nodes of the middle layer; measuring similarity distances for a first entity as compared to other entities of the set of entities based on distance between the corresponding values at the middle layer; identifying a similar entity to the first entity based on the measured similarity distance for the first entity to the similar entity being the shortest of the measured similarity distances; and providing a recommendation for a computer application for the first entity based on the similar entity.

Abstract: Systems, methods and computer readable medium are provided for receiving a first set of recommendations of computer applications from a recommendations engine having an input layer, at least one hidden layer and an output layer, the recommendations generated based on a set of input features characterizing an entity; identifying a commonality among at least some recommendations for defining a priority trait for the entity; associating the priority trait with at least one priority feature from the set of input features; generating a modification for modifying at least one of: the set of input features provided as input to the recommendations engine to emphasize those features associated with the priority feature, or at least one weight of the hidden layer in the recommendations engine to bias selection of the priority feature; providing the modification to the recommendations engine to generate a second set of recommendations for display on a computing device.