US 10,757,530 B1Granted

Computer model accuracy in predicting location of online system users

AssigneeFacebook, Inc.

InventorsTom Susel, Benjamin Tucker Savage

Life of this patent

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Abstract

An online system receives a request from a user of a manager transmitter to generate a unique beacon identifier (ID) associated with a physical location. Responsive to receiving the beacon ID from the online system, the manager transmitter transmits a Bluetooth signal comprising the beacon ID to user client devices, which send the beacon ID to the online system for identification. Responsive to detecting that a received signal strength exceeds a threshold, a location context module classifies the instance of the user client device detecting the signal as an example of a user being present at the physical location. A location prediction module uses the instance as training data to train a machine-learning model to predict the presence of online system users at the physical location.

Claims20

Dependent claims

A method comprising:

receiving, by an online system, from a first client device associated with a first user of an online system, a request to identify a short-range radio signal;
identifying, by the online system, the short-range radio signal as associated with a physical location;
responsive to detecting that a signal strength associated with the short-range radio signal exceeds a threshold, classifying, by the online system, the first client device as present at the physical location;
receiving, by the online system, a first set of context information comprising signals received by the first client device when present at the physical location;
and
training, by the online system, a machine-learning model using training data including the first set of context information to predict a likelihood that a second user of the online system is present at the physical location based on a second set of context information comprising signals received from a second client device associated with the second user.

3 more elements

A non-transitory computer readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations comprising:

receiving, by an online system, from a first client device associated with a first user of an online system, a request to identify a short-range radio signal;
identifying, by the online system, the short-range radio signal as associated with a physical location;
responsive to detecting that a signal strength associated with the short-range radio signal exceeds a threshold, classifying, by the online system, the first client device as present at the physical location;
receiving, by the online system, a first set of context information comprising signals received by the first client device when present at the physical location;
and
training, by the online system, a machine-learning model using training data including the first set of context information to predict a likelihood that a second user of the online system is present at the physical location based on a second set of context information comprising signals received from a second client device associated with the second user.

3 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/234,428Filed 27 Dec 2018 · continuation
Priority: 21 Sep 2017
Granted: 25 Aug 2020
Term ends: Not estimatedThe source records don’t support an estimate.

Classification8 codes

H04W 4/02
Services specially adapted for wireless communication networks; Facilities therefor: services making use of location information
G06N 20/00
Machine learning
H04W 64/003
Locating users or terminals or network equipment for network management purposes, e.g. mobility management: locating network equipment
H04W 88/08
Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices: access point devices