Generative content system that supports location-based services and methods therefor

A generative content system that performs location-based services, the generative content system comprising:

• one or more processing devices;
• memory that stores a plurality of computer-executable instructions that, when executed by the one or more processing devices, cause the one or more processing devices to:
• receive a plurality of samples corresponding to an area to be sampled, wherein the plurality of samples are received from a plurality of different devices, wherein each sample is received from a respective device of the plurality of different devices and indicates a location at which the sample was taken, one or more network identifiers of respective network detected by the respective device, and, for each network identifier, a signal strength of a signal received from the respective network as measured by the device at the location;
• generate a plurality of sample nodes based on the plurality of samples, wherein each sample node corresponds to a respective sample from the plurality of samples and indicates the location at which the sample was taken, the one or more network identifiers detected at the location when the sample was taken, and the one or more signal strengths at the location;
• generate a graph based on the plurality of sample nodes, wherein the graph connects the sample nodes to point of interest nodes, wherein each point of interest node corresponds to a point of interest within the area;
• generate a simulated sample node based on an analysis of the graph, wherein the synthesized sample node indicates simulated sample data generated in response to identifying a missing signal strength or an outlier signal strength corresponding to a particular point of interest;
• update the graph with the simulated sample node;
• generate a training data set based on the updated graph, wherein the training data set includes the simulated sample data;
• train a machine-learned classification model based on the training data, wherein the machine-learned classification model is configured to receive signal profiles indicating detected network identifiers and measured signal strengths corresponding to the detected network identifiers and to output one or more candidate locations within the area and, for each candidate location, a confidence score corresponding to the candidate location, wherein each candidate location corresponds to a different point of interest within the area;
• and
• store the machine-learned model in a datastore, the machine-learned classification model being used in location-based services corresponding to the area.