# US 12,182,738 B2 · Active notification using transportation service prediction

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- Number: US 12,182,738 B2
- Document ID: US12182738B2
- Status: Granted
- Kind: B2
- Application number: 18/490,322
- Filed: 2023-10-19
- Published: 2024-02-08
- Granted: 2024-12-31
- Earliest claimed: 2020-09-22
- Assignees: Uber Technologies, Inc.
- Applicants: Uber Technologies, Inc.
- Inventors: Neil Chagas Fernandes; Aditya Somani; Adnan Akil; Pablo Bellver; Jieying Chen; Archisman Roy; Gustavo Bagdadi de Castro; Norbert Y. Hu; Talal Toukan; Lu Huang; Yuh-Jie Eunice Chen
- Web page: https://patentgrep.com/patent/US12182738B2

## CPC

- G06Q 10/02: Reservations, e.g. for tickets, services or events
- G06Q 30/0261: {based on user location}
- G06N 20/00: Machine learning
- G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202)
- G06Q 30/0253: {During e-commerce, i.e. online transactions}
- G06Q 30/0267: {Wireless devices}
- G06Q 30/0271: {Personalized advertisement}
- G06Q 30/0631: {Recommending goods or services}
- G06Q 50/40: Business processes related to the transportation industry (shipping G06Q10/083)
- H04W 4/025: {using location based information parameters}
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)

## Abstract

Systems and methods of generating active notifications for users of a networked computer system using transportation service prediction are disclosed herein. In some example embodiments, a computer system uses a prediction model to generate a transportation service prediction for a user based on an identification of the user, location data for the user, prediction time data, and historical user data for instances of the user using the transportation, and then causes a notification to be displayed on a computing device of the user based on the transportation service prediction, with the notification indicating a recommended use of the transportation service in association with the place for the time of day and the day of the week, and the notification comprising a selectable user interface element configured to enable the user to submit an electronic request for the recommended use of the transportation service.

## Claims

### Claim 1

A computer-implemented method performed by at least one hardware processor, the computer-implemented method comprising:
receiving an identification of a target user, user location data via a GPS signal from a mobile device of the target user indicating a location associated with the target user, prediction time data indicating a time of day and a day of the week for which a transportation service prediction is to be generated, and historical user data indicating a plurality of instances of the target user using a transportation service in association with a place, the historical user data indicating a corresponding time of day and a corresponding day of the week for each one of the plurality of instances of the target user using the transportation service;
generating the transportation service prediction for the target user based on the identification of the target user, the user location data, the prediction time data, and the historical user data using a prediction model, the transportation service prediction indicating a probability that the target user will request the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data; and
transmitting a notification from a networked computer system to the mobile device of the target user causing the notification to be displayed on the mobile device of the target user based on the transportation service prediction for the target user and on a determination that a current location of the target user is not within a minimum threshold distance from the place, the notification indicating a recommended use of the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data, and the notification comprising a selectable user interface element configured to enable the target user to submit an electronic request for the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data.

### Claim 2 (depends on 1)

The computer-implemented method of claim 1, further comprising:
identifying a plurality of candidate service clusters, each one of the plurality of candidate service clusters being defined by a corresponding service configuration, the corresponding service configuration comprising an origin location, a destination location, a window of time, a day of the week, and a type of transportation service, and each one of the plurality of candidate service clusters being identified based on a determination that a reference user of the networked computer system used the networked computer system in accordance with the corresponding service configuration in a number of service instances that satisfies a repeat criteria;
obtaining training data comprising, for each one of the plurality of candidate service clusters, a corresponding record of how often the reference user used the networked computer system in accordance with the corresponding service configuration and historical user data of the reference user indicating a plurality of instances of the reference user using the transportation service, the historical user data of the reference user indicating a corresponding time of day and a corresponding day of the week for each one of the plurality of instances of the reference user using transportation service; and
training the prediction model with the training data using a machine learning algorithm.

### Claim 3 (depends on 1)

The computer-implemented method of claim 1, wherein the location associated with the target user comprises a current location of the target user determined based on a current location of the mobile device of the target user via the GPS signal.

### Claim 4 (depends on 1)

The computer-implemented method of claim 1, wherein the transportation service comprises transportation of a person or transportation of one or more goods.

### Claim 5 (depends on 1)

The computer-implemented method of claim 1, wherein the prediction model is selected from a group of models consisting of a logistic regression model, a decision tree model, a bagging model, a boosting model, and an ensemble model.

### Claim 6 (depends on 1)

The computer-implemented method of claim 1, wherein:
the generating the transportation service prediction comprises using the prediction model to generate the probability that the target user will request the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data;
the causing the notification to be displayed on the mobile device of the target user comprises determining that the generated probability satisfies a probability threshold value; and
the causing the notification to be displayed on the mobile device of the target user is further based on the determination that the generated probability satisfies the probability threshold value.

### Claim 7 (depends on 1)

The computer-implemented method of claim 1, wherein the causing the notification to be displayed on the mobile device of the target user is further based on a determination that the target user has not requested the transportation service via the networked computer system within a predetermined amount of time of a current time.

### Claim 8 (depends on 1)

The computer-implemented method of claim 1, wherein the causing the notification to be displayed on the mobile device of the target user is further based on a determination that the target user is not currently using the transportation service of the networked computer system.

### Claim 9 (depends on 1)

The computer-implemented method of claim 1, wherein the causing the notification to be displayed on the mobile device of the target user is further based on a determination that a mobile application of the networked computer system is not currently open in a foreground of the mobile device of the target user.

### Claim 10 (depends on 1)

The computer-implemented method of claim 1, wherein the causing the notification to be displayed on the mobile device of the target user is further based on a determination that a current location of the target user is not outside of a maximum threshold distance from the place.

### Claim 11 (depends on 1)

The computer-implemented method of claim 1, wherein the causing the notification to be displayed on the mobile device of the target user is further based on a determination that the day of the week indicated by the prediction time data is not included in an exclusion list, the exclusion list comprising at least one day of the week or at least one calendar date on which the notification is to be prevented from being displayed to the target user.

### Claim 12 (depends on 1)

The computer-implemented method of claim 1, wherein the selectable user interface element of the notification is configured to, in response to its selection, automatically configure the electronic request for the transportation service.

### Claim 13 (depends on 1)

The computer-implemented method of claim 1, wherein the notification is displayed on a lock screen of the mobile device.

### Claim 14

A system comprising:
at least one hardware processor; and
a machine storage medium embodying a set of instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform operations comprising:
receiving an identification of a target user, user location data via a GPS signal from a mobile device of the target user indicating a location associated with the target user, prediction time data indicating a time of day and a day of the week for which a transportation service prediction is to be generated, and historical user data indicating a plurality of instances of the target user using a transportation service in association with a place, the historical user data indicating a corresponding time of day and a corresponding day of the week for each one of the plurality of instances of the target user using the transportation service;
generating the transportation service prediction for the target user based on the identification of the target user, the user location data, the prediction time data, and the historical user data using a prediction model, the transportation service prediction indicating a probability that the target user will request the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data; and
transmitting a notification from a networked computer system to the mobile device of the target user causing the notification to be displayed on the mobile device of the target user based on the transportation service prediction for the target user and on a determination that a current location of the target user is not within a minimum threshold distance from the place, the notification indicating a recommended use of the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data, and the notification comprising a selectable user interface element configured to enable the target user to submit an electronic request for the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data.

### Claim 15 (depends on 14)

The system of claim 14, wherein the operations further comprise:
identifying a plurality of candidate service clusters, each one of the plurality of candidate service clusters being defined by a corresponding service configuration, the corresponding service configuration comprising an origin location, a destination location, a window of time, a day of the week, and a type of transportation service, and each one of the plurality of candidate service clusters being identified based on a determination that a reference user of the networked computer system used the networked computer system in accordance with the corresponding service configuration in a number of service instances that satisfies a repeat criteria;
obtaining training data comprising, for each one of the plurality of candidate service clusters, a corresponding record of how often the reference user used the networked computer system in accordance with the corresponding service configuration and historical user data of the reference user indicating a plurality of instances of the reference user using the transportation service, the historical user data of the reference user indicating a corresponding time of day and a corresponding day of the week for each one of the plurality of instances of the reference user using transportation service; and
training the prediction model with the training data using a machine learning algorithm.

### Claim 16 (depends on 14)

The system of claim 14, wherein the location associated with the target user comprises a current location of the target user determined based on a current location of the mobile device of the target user via the GPS signal.

### Claim 17 (depends on 14)

The system of claim 14, wherein the transportation service comprises transportation of a person or transportation of one or more goods.

### Claim 18 (depends on 14)

The system of claim 14, wherein:
the generating the transportation service prediction comprises using the prediction model to generate the probability that the target user will request the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data;
the causing the notification to be displayed on the mobile device of the target user comprises determining that the generated probability satisfies a probability threshold value; and
the causing the notification to be displayed on the mobile device of the target user is further based on the determination that the generated probability satisfies the probability threshold value.

### Claim 19 (depends on 14)

The system of claim 14, wherein the causing the notification to be displayed on the mobile device of the target user is further based on a determination that the target user has not requested the transportation service via the networked computer system within a predetermined amount of time of a current time.

### Claim 20

A non-transitory machine storage medium embodying a set of instructions that, when executed by at least one hardware processor, cause the processor to perform operations comprising:
receiving an identification of a target user, user location data via a GPS signal from a mobile device of the target user indicating a location associated with the target user, prediction time data indicating a time of day and a day of the week for which a transportation service prediction is to be generated, and historical user data indicating a plurality of instances of the target user using a transportation service in association with a place, the historical user data indicating a corresponding time of day and a corresponding day of the week for each one of the plurality of instances of the target user using the transportation service;
generating the transportation service prediction for the target user based on the identification of the target user, the user location data, the prediction time data, and the historical user data using a prediction model, the transportation service prediction indicating a probability that the target user will request the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data; and
transmitting a notification from a networked computer system to the mobile device of the target user causing the notification to be displayed on the mobile device of the target user based on the transportation service prediction for the target user and on a determination that a current location of the target user is not within a minimum threshold distance from the place, the notification indicating a recommended use of the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data, and the notification comprising a selectable user interface element configured to enable the target user to submit an electronic request for the transportation service in association with the place for the time of day and the day of the week indicated by the prediction time data.