Systems for predicting and classifying location data based on machine learning
Abstract:
Systems and methods can use a variety of computing devices to obtain location data that can be used to generate a prediction of a likelihood that a person will move his or her residence. The location data can be generated based on location data captured from a mobile computing device and/or based on telematics data captured during the operation of a vehicle and/or from a computing device. The location data may be compiled into graphs comprising locations of visited by the person and relationships between the locations visited by the person, such as instances of the person traveling between the two locations. The likelihood to change residence can be determined based on the amount of time the person spent at a given location, the distance between the various locations that are the most significant in the graph, and/or the frequency of visits to particular locations.
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