Automatic selection of dynamic data entries for multiple dynamic databases

A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to:

• maintain time-sensitive datasets associated with a plurality of branch locations associated with a third-party system, wherein each time-sensitive dataset tracks a plurality of dynamic item entries that vary in a course of an operation of a particular branch location;
• access a machine learning model trained to predict a metric value representing a size of dynamic item entries available, wherein the machine learning model was trained by:
• obtaining training datasets of historical transactions at a plurality of geographical locations, the training datasets including weighted values associated with items at the geographical locations;
• forward propagating data from the training datasets through the machine learning model to generate predicted metric values;
• backpropagating the predicted metric values through the machine learning model to adjust weights of the machine learning;
• and
• saving the adjusted item availability model;
• receive a selection of the dynamic item entries from a user device, the selection being in association with a session in which the user device requests for a physical arrangement between an agent and the third-party system at a branch location;
• retrieve a geographical location associated with the user device;
• determine a subset of the branch locations associated with the third-party system that are eligible for further selection based on distances of the branch locations from the geographical location associated with the user device;
• determine, using the trained machine learning model, for each branch location in the subset, a metric measuring a size of the dynamic item entries available in the time-sensitive dataset corresponding to the branch location;
• and
• select one of the branch locations in the subset based on the metric for carrying out the physical arrangement.

An system comprising:

• a processor;
• and
• memory configured to store code comprising instructions, the instructions, when executed by the processor, cause the processor to:
• maintain time-sensitive datasets associated with a plurality of branch locations associated with a third-party system, wherein each time-sensitive dataset tracks a plurality of dynamic item entries that vary in a course of an operation of a particular branch location;
• access a machine learning model trained to predict a metric value representing a size of dynamic item entries available, wherein the machine learning model was trained by:
• obtaining training datasets of historical transactions at a plurality of geographical locations, the training datasets including weighted values associated with items at the geographical locations;
• forward propagating data from the training datasets through the machine learning model to generate predicted metric values;
• backpropagating the predicted metric values through the machine learning model to adjust weights of the machine learning;
• and
• saving the adjusted item availability model;
• receive a selection of the dynamic item entries from a user device, the selection being in association with a session in which the user device requests for a physical arrangement between an agent and the third-party system at a branch location;
• retrieve a geographical location associated with the user device;
• determine a subset of the branch locations associated with the third-party system that are eligible for further selection based on distances of the branch locations from the geographical location associated with the user device;
• determine, using the trained machine learning model, for each branch location in the subset, a metric measuring a size of the dynamic item entries available in the time-sensitive dataset corresponding to the branch location;
• and
• select one of the branch locations in the subset based on the metric for carrying out the physical arrangement.