Dynamic coordination of service providers and service seeking entities

A computer program product comprising:

• a program of instructions tangibly embodied on a non-transitory computer readable medium wherein, when the instructions are executed on a processor, the processor causes operations to be performed to automatically prioritize predicted events in a dynamic predicted queueing profile data structure for a service provider for a finite future time period, the operations comprising:
• generate, by the processor, in response to receiving a request signal originating from a first device associated with a first service seeking entity and representing a request for service from the first service seeking entity seeking service from a first service provider at a first future time period, a first dynamic queueing event profile comprising an association of the first service seeking entity with a first predicted queueing profile for the first service provider at the first future time period, wherein the first predicted queueing profile is stored in a first datastore and corresponds to a single time block for providing a service sought by the service seeking entity, and wherein the first predicted queueing profile comprises associations with a plurality of dynamic queueing event profiles associating a corresponding service seeking entity and the first service provider with the first predicted queueing profile for the first future time period, wherein the plurality of dynamic queueing event profiles are stored in a second at least one data store, and wherein the plurality of dynamic queueing event profiles comprises the first dynamic queueing event profiles;
• retrieve, from a third at least one data store, by the processor, a predetermined historical behavior profile of the first service provider and a predetermined historical behavior profile of the first service seeking entity;
• generate, by an execution confidence engine, for each of the plurality of dynamic queueing event profiles associated with the first predicted queueing profile, a confidence level of execution that the service seeking entity will receive service from the service provider in the first future time period represented by the single time block, wherein the confidence level of execution is based at least on an execution confidence model generated by a machine learning algorithm, current geolocation coordinates of the first service seeking entity in a predetermined time window before the future time period of the first predicted queueing profile, a historical behavior profile of the first service provider, a historical behavior profile of the corresponding service seeking entity, and a historical behavior profile of at least one service seeking entity associated with the plurality of dynamic queueing event profiles other than the first dynamic queueing event profile;
• apply a dynamic queueing engine to each of the plurality of dynamic queueing event profiles to determine based on the corresponding confidence level of execution for each of the plurality of dynamic queueing event profiles, a corresponding priority in the first predicted queueing profile;
• associate the first dynamic queueing event profile with the corresponding priority in the first predicted queueing profile such that the first dynamic queueing event profile is automatically prioritized in the first predicted queueing profile as a function of the corresponding historical behavior profile of the first service seeking entity and the historical behavior profile of the first service provider;
• in response to an update signal corresponding to at least one of the first dynamic queueing event profile and the first predicted queueing profile, repeat the steps of generate a confidence level of execution and apply the dynamic queueing engine such that the first dynamic queueing event profile is automatically dynamically reprioritized in the first predicted queueing profile;
• when the confidence level of execution for the first dynamic queueing event profile in the first predicted queueing profile meets at least one predetermined criterion, then generate a signal to associate the first dynamic queueing event profile—with a guaranteed status in the first predicted queueing profile;
• generate a display signal configured to induce the first device to generate a graphical display based on the confidence level of execution corresponding to at least one of the plurality of predicted queueing profiles corresponding to at least one future finite time period;
• and,
• in response to a training signal, perform training operations to retrain the execution confidence model by a machine learning algorithm, wherein the training operations are applied repeatedly until an accuracy score meets at least one predetermined accuracy criterion, wherein the accuracy score is generated as a function of an output generated based on a predetermined set of requests for service by the retrained executed confidence model and a target outcome of the predetermined set of requests.