System and method for matching integration process management system users using deep learning and matrix factorization

A method of matching integration process users comprising:

• receiving, via a network interface device, a plurality of execution logs recording data for tracking selections of integration process visual elements by a plurality of users for developing integration processes;
• generating, via a processor, a user/visual element interaction matrix based on a plurality of counts of integration process visual element selections;
• inputting the user/visual element interaction matrix into a trained neural network to generate a neural network output used for determining a latent feature user preference value to adapt positive user feedback to incorporate negative feedback of selection or non-selection by users for the integration process visual elements;
• identifying a subset of matching users associated with latent feature user preference values for one of the plurality of integration process visual elements falling within a preset range of each other as matching users;
• and
• transmitting, via the network interface device, identification of the subset of matching users and identification of the one of the plurality of integration process visual elements to at least one matched user.

An information handling system operating an integration process user matching system comprising:

• a network interface device receiving a plurality of execution logs recording data for tracking selections of integration process visual elements by a plurality of users for developing integration processes;
• a processor training a neural network, based on a test user/visual element interaction matrix, a validation user/visual element interaction matrix, and an initial preset latent features value to increase correlation between test latent features user preference values determined based on the test user/visual element interaction matrix and validation latent features user preference values for optimizing accuracy of user preference assessments to improve user matching;
• the processor generating a matching assessment user/visual element interaction matrix based on a plurality of counts of integration process visual element selections received after training the neural network and inputting the matching assessment user/visual element interaction matrix into a trained neural network to generate a neural network output;
• the processor determining a latent feature user preference value to incorporate negative feedback of the plurality of users for each of the plurality of integration process visual elements based on the neural network output;
• the processor identifying a subset of matching users associated with latent feature user preference values for one of the plurality of integration process visual elements falling within a preset range of each other as matching users;
• and
• the network interface device transmitting identification of the subset of matching users and identification of the one of the plurality of integration process visual elements to at least one matching user.