Identification of location-tracked audiences
AssigneeMobile Technology Corporation
InventorsStephen Skory, Michael Perri, Dale Hartzell, Nicholas Connor
Life of this patent
Estimating the term…
Abstract
Disclosed herein identifies audiences of mobile devices that behave a like a seed group of devices. That is, the behave alike group are those devices that move in similar patterns and visit the similar locations with a similar frequency as the devices of the seed group. Similarity is based on correlative similarity in having visited matching categories of location styles identified via mapping data (e.g., devices that visit national parks at a similar frequency). Correlative similarity is performed using a machine learning model trained via a follow the regularized leader proximal.
Claims22
A method of identifying users of mobile devices of a population that are similar to a seed group of users of mobile devices, comprising:
- generating device behavior profiles associated with a population of mobile devices, wherein the device behavior profiles include location data of the population of mobile devices over a time period on multiple occasions, the location data including a plurality of coordinates attributed to addresses visited by each respective mobile device of the population of mobile devices;
- assigning the addresses visited by each respective mobile device into categories based on a purpose of structures at each given address;
- and
- identifying a subset of the population of mobile devices that are correlatively similar to a seed group of mobile devices based on a relationship to the categories assigned to locations visited by each respective device.
A system of identifying users of mobile devices of a population that behave similarly to a seed group of users of mobile devices, comprising:
- a memory including a plurality of device behavior profiles associated with a population of mobile devices, wherein the device behavior profiles include location data of the population of mobile devices over a time period on multiple occasions, the location data including a plurality of coordinates attributed to addresses visited by each respective mobile device of the population of mobile devices, wherein the plurality of device behavior profiles include assignment of the addresses visited by each respective mobile device into categories based on a purpose of structures at each given address;
- and
- a trained machine learning model that identifies a subset of the population of mobile devices that are correlatively similar to a seed group of mobile devices based on a relationship to the categories assigned to locations visited by each respective device.
A computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform a process comprising:
- generating device behavior profiles associated with a population of mobile devices, wherein the device behavior profiles include location data of the population of mobile devices over a time period on multiple occasions, the location data including a plurality of coordinates attributed to addresses visited by each respective mobile device of the population of mobile devices;
- assigning the addresses visited by each respective mobile device into categories based on a purpose of structures at each given address;
- and
- identifying a subset of the population of mobile devices that are correlatively similar to a seed group of mobile devices based on a relationship to the categories assigned to locations visited by each respective device.
Dependencies are inferred from the claim text.