# US 2019/0171733 A1 · Point of interest accuracy using tickets

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2019/0171733 A1
- Document ID: US20190171733A1
- Status: Published application
- Kind: A1
- Application number: 15/829,634
- Filed: 2017-12-01
- Published: 2019-06-06
- Earliest claimed: 2017-12-01
- Assignees: Uber Technologies, Inc.
- Applicants: Uber Technologies, Inc.
- Inventors: Alvin AuYoung; Sheng Yang; Chandan Sheth; Chun-Chen Kuo; Livia Zarnescu Yanez; Shivendra Pratap Singh; Vikram Saxena
- Web page: https://patentgrep.com/patent/US20190171733A1

## CPC

- G06F 16/29: Geographical information databases
- G06F 16/2365: {Ensuring data consistency and integrity}
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N 20/00: Machine learning
- G06F 2216/03: Data mining
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

Systems and methods for improving accuracy of geographic position data are provided. A networked system mines ticket data from content of the ticket. Based on the ticket data, a determination is made that the ticket indicates an issue with a trip involving a point of interest (POI). The networked system extracts trip data from a trip log corresponding to the trip involving the POI, and identifies, from a data storage, stored attributes of the POI. The networked system analyzes the ticket data, trip data, and attributes to determine a workflow to improve accuracy of the POI, whereby the analyzing comprises determining a priority level to verify accuracy of the POI. The workflow is triggered based on the priority level to verify accuracy of the POI.

## Claims

### Claim 1

A system comprising:
one or more hardware processors; and
a memory storing instructions that, when executed by the one or more hardware processors, causes the one or more hardware processors to perform operations comprising:
mining ticket data from content of the ticket;
determining, based on the ticket data, that the ticket indicates an issue with a trip involving a point of interest (POI);
extracting trip data from a trip log corresponding to the trip involving the POI;
identifying, from a data storage, stored attributes of the POI;
analyzing the ticket data, trip data, and attributes to determine a workflow to improve accuracy of the POI, the analyzing comprising determining a priority level to verify accuracy of the POI, the workflow being based on the priority level to verify accuracy of the POI; and
triggering a workflow process based on the priority level.

### Claim 2 (depends on 1)

The system of claim 1, wherein the priority level is high, and the workflow process comprises triggering an operator to verify the accuracy of the POI.

### Claim 3 (depends on 1)

The system of claim 1, wherein the priority level is medium, and the workflow process comprises triggering a user generated content (UGC) process, the UGC process comprising:
causing a user interface to be presented on a user device of a user that has an association with the POI, the user interface presenting a query regarding verifying the address;
receiving a response to the query via the user interface from the user device; and
using the response to verify the address.

### Claim 4 (depends on 1)

The system of claim 1, wherein the priority level is low, and the workflow process comprises storing the ticket data to the data storage in response to the priority level being low.

### Claim 5 (depends on 1)

The system of claim 1, wherein the determining that the ticket indicates an issue with a trip involving the POI comprises applying a classification model to the ticket data to determine a probability that the ticket is associated with the POI.

### Claim 6 (depends on 5)

The system of claim 5, wherein the classification model comprises a logistic regression model.

### Claim 7 (depends on 1)

The system of claim 1, wherein the mining ticket data from the content of the ticket comprises applying a natural language processing model to the ticket.

### Claim 8 (depends on 1)

The system of claim 1, wherein the extracting trip data from the trip log comprises detecting a change in routing during the trip or a drop-off location a threshold distance from an entered destination.

### Claim 9 (depends on 1)

The system of claim 1, wherein the determining the priority level comprises determining a priority score, the determining the priority score being based on one or more of a weighted average of trip counts to the POI; a weight average of trip cost to the POI, a metric of a category assigned to the POI, or a metric of likelihood of non-retention of a user associated with the ticket.

### Claim 10 (depends on 1)

The system of claim 1, wherein the analyzing further comprises determining, using a deep learning model, an accuracy score based on a sequence of characters from the ticket.

### Claim 11

A method comprising:
mining ticket data from content of the ticket;
determining, based on the ticket data, that the ticket indicates an issue with a trip involving a point of interest (POI);
extracting trip data from a trip log corresponding to the trip involving the POI;
identifying, from a data storage, stored attributes of the POI;
analyzing, by one or more hardware processors, the ticket data, trip data, and attributes to determine a workflow to improve accuracy of the POI, the analyzing comprising determining a priority level to verify accuracy of the POI, the workflow being based on the priority level to verify accuracy of the POI; and
triggering a workflow process based on the priority level.

### Claim 12 (depends on 11)

The method of claim 11, wherein the priority level is high, and the workflow process comprises triggering an operator to verify the accuracy of the POI.

### Claim 13 (depends on 11)

The method of claim 11, wherein the priority level is medium, and the workflow process comprises triggering a user generated content (UGC) process, the UGC process comprising:
causing a user interface to be presented on a user device of a user that has an association with the POI, the user interface presenting a query regarding verifying the address;
receiving a response to the query via the user interface from the user device; and
using the response to verify the address.

### Claim 14 (depends on 11)

The method of claim 11, wherein the priority level is low, and the workflow process comprises storing the ticket data to the data storage in response to the priority level being low.

### Claim 15 (depends on 11)

The method of claim 11, wherein the determining that the ticket indicates an issue with a trip involving the POI comprises applying a classification model to the ticket data to determine a probability that the ticket is associated with the POI.

### Claim 16 (depends on 15)

The method of claim 15, wherein the classification model comprises a logistic regression model or a classification tree model.

### Claim 17 (depends on 11)

The method of claim 11, wherein the extracting trip data from the trip log comprises detecting a change in routing during the trip or a drop-off location a threshold distance from an entered destination.

### Claim 18 (depends on 11)

The method of claim 11, wherein the determining the priority level comprises determining a priority score, the determining the priority score being based on one or more of a weighted average of trip counts to the POI; a weight average of trip cost to the POI, a metric of a category assigned to the POI, or a metric of likelihood of non-retention of a user associated with the ticket.

### Claim 19 (depends on 11)

The method of claim 11, wherein the analyzing further comprises determining, using a deep learning model, an accuracy score based on a sequence of characters from the ticket.

### Claim 20

A machine-storage medium storing instructions that, when executed by one or more processors of a machine, cause the one or more processors to perform operations comprising:
mining ticket data from content of the ticket:
determining, based on the ticket data, that the ticket indicates an issue with a trip involving a point of interest (POI);
extracting trip data from a trip log corresponding to the trip involving the POI;
identifying, from a data storage, stored attributes of the POI;
analyzing the ticket data, trip data, and attributes to determine a workflow to improve accuracy of the POI, the analyzing comprising determining a priority level to verify accuracy of the POI, the workflow being based on the priority level to verify accuracy of the POI; and
triggering a workflow process based on the priority level.