Validating hours of operation

• US 9,704,164 B2
• Filed: 06/13/2013
• Issued: 07/11/2017
• Est. Priority Date: 06/13/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Wuest, Brandon Stephen
• Primary Examiner(s): Fleischer, Mark A
• Application Number:
  US13/917,576
• Publication Number:
  US 20150170156A1
• Time in Patent Office: 1,489 Days
• Field of Search: 726 25, 726 17, 726 19, 726 5
• CPC Class Codes: G06Q 30/018 Certifying business or products

Abstract

A system for validating hours of operation may include one or more computing devices and a memory. The one or more computing devices may receive hours of operation of a business for a day of a week and receive data items that are associated with a time of the day of the week, wherein the data items are also associated with the business being open or closed at the associated time of the day of the week. The one or more computing devices may determine, based at least in part on the data items, a likelihood that the hours of operation of the business for the day of the week are inaccurate. The one or more computing devices may provide to an electronic device associated with the business an indication that the hours of operation for the day of the week are likely inaccurate when the likelihood satisfies a threshold.

Claims

1. A computer-implemented method for validating hours of operation of a business, the method comprising:

receiving, by one or more computing devices, hours of operation of a business for a day of a week;

receiving, by the one or more computing devices, a plurality of data items that are each associated with a time of the day of the week, wherein each of the plurality of data items is reflective of, or evidence of, an operational status of business at the associated time of the day of the week, wherein each of the plurality of data items is received from one or more servers and is indicative of a user request for interaction with the business or a user interaction with the business from positioning information received from a mobile device associated with a user;

determining, by the one or more computing devices, based at least in part on the operational status of the business that is reflected, or evidenced, by each of the plurality of data items, a likelihood that the hours of operation of the business for the day of the week are inaccurate, wherein the plurality of data items are associated with a plurality of weights and the determining further comprises determining, by the one or more computing devices and based at least in part on the operational status of the business that is reflected, or evidenced, by each of the plurality of data items and the associated plurality of weights, the likelihood that the hours of operation of the business for the day of the week are inaccurate; and

providing, by the one or more computing devices, to a first electronic device comprising a mobile device associated with the business, a user interface having a first indication that the hours of operation for the day of the week are likely inaccurate when the likelihood exceeds a threshold such that the first electronic device displays the first indication alongside the hours of operation of the business in the user interface to a user of the first electronic device.

2. The computer-implemented method of claim 1, wherein the providing the first indication that the hours of operation for the day of the week are inaccurate comprises:

generating, by the one or more computing devices, an estimated hours of operation for the day of the week based at least in part on the operational status of the business that is reflected, or evidenced, by each of the plurality of data items; and

providing, by the one or more computing devices, the estimated hours of operation for the day of the week.

3. The computer-implemented method of claim 2, further comprising:

receiving, by the one or more computing devices and in response to providing the estimated hours of operation for the day of the week, a confirmation that the hours of operation of the business for the day of the week are inaccurate; and

correcting, by the one or more computing devices, the hours of operation of the business for the day of the week based at least in part on the estimated hours of operation for the day of the week.

4. The computer-implemented method of claim 2, further comprising:

receiving, by the one or more computing devices and from a second electronic device associated with a user, a request for the hours of operation for the business;

providing, by the one or more computing devices and to the second electronic device, the hours of operation for the business for the day of the week; and

providing, by the one or more computing devices and to the second electronic device the estimated hours of operation for the business for the day of the week when the likelihood satisfies a threshold.

5. The computer-implemented method of claim 4, wherein the request for the hours of operation for the business is received on the day of the week and further comprising:

determining, by the one or more computing devices, a time that the request was received;

providing, by the one or more computing devices and to the second electronic device, a second indication that the business is open when the hours of operation of the business and the estimated hours of operation of the business both indicate that the business is open at the time that the request was received;

providing, by the one or more computing devices and to the second electronic device, a third indication that the business is closed when the hours of operation of the business and the estimated hours of operation of the business both indicate that the business is closed at the time that the request was received;

providing, by the one or more computing devices and to the second electronic device, a fourth indication that the business may be open when the hours of operation indicate that the business is closed and the estimated hours of operation indicate that the business is open; and

providing, by the one or more computing devices and to the second electronic device, a fifth indication that the business may be closed when the hours of operation indicate that the business is open and the estimated hours of operation indicate that the business is closed.

6. The computer-implemented method of claim 1, wherein the hours of operation of the business for the day of the week comprise an opening time and a closing time.

7. The computer-implemented method of claim 6, wherein the likelihood that the hours of operation of the business for the day of the week are inaccurate satisfies the threshold when a number of the data items indicate that the business is open later than the closing time, that the business is open earlier than the opening time, that the business is closed earlier than the closing time, or that the business is closed later than the opening time.

8. The computer-implemented method of claim 1, wherein the receiving the plurality of data items that are each associated with the time of the day of the week comprises:

receiving, by the one or more computing devices, a second indication that an employee of the business is at a location of the business.

9. The computer-implemented method of claim 8, wherein the receiving the plurality of data items that are each associated with the time of the day of the week comprises:

receiving, by the one or more computing devices, a third indication that a non-employee is at the location of the business.

10. The computer-implemented method of claim 1, further comprising:

receiving, by the one or more computing devices, a plurality of hours of operation of a plurality of other businesses for the day of the week, wherein each of the plurality of other businesses is associated with a business category;

determining, by the one or more computing devices and based at least in part on the plurality of hours of operation of the plurality of other businesses, a profile hours of operation for the business category;

determining, by the one or more computing devices, whether the hours of operation of the business for the day of the week coincide with the profile hours of operation; and

providing, by the one or more computing devices and to the first electronic device associated with the business, a first suggestion to associate the business with the business category when the received hours of operation of the business coincide with the profile hours of operation of the business category and the business is not associated with the business category.

11. The computer-implemented method of claim 10, further comprising:

providing, by the one or more computing devices and to the first electronic device associated with the business, a second suggestion that the hours of operation of the business should be modified to conform to the profile hours of operation of the business category when the hours of operation of the business do not coincide with the profile hours of operation and the business is associated with the business category.

12. The computer-implemented method of claim 10, further comprising:

determining, by the one or more computing devices, at least one of the plurality of other businesses associated with the business category for which the hours of operation do not coincide with the profile hours of operation; and

providing, by the one or more computing devices, a second suggestion that the at least one of the plurality of other businesses should conform to the profile hours of operation or be disassociated with the business category.

13. A non-transitory machine readable medium embodying instructions that, when executed by a machine, cause the machine to perform a method for providing suggested hours of operation for a business, the method comprising:

receiving hours of operation of a business for a day of a week;

receiving a plurality of data items that are each associated with a time of the day of the week, wherein each of the plurality of data items is received from one or more servers and is indicative of a user request for interaction with the business or a user interaction with the business from positioning information received from a mobile device associated with a user, wherein the hours of operation of the business for the day of the week comprise an opening time and a closing time and wherein each of the plurality of data items is indicative of the user request for interaction with the business, the time of the day of the week associated with each of the plurality of data items being generated before the opening time of the business or after the closing time of the business;

determining, based at least in part on the plurality of data items and a plurality of weights associated with the plurality of data items, a modified hours of operation of the business for the day of the week and an earlier opening time for the day of the week or a later closing time for the day of the week; and

providing to a mobile device for display a user interface having an indication of the modified hours of operation of the business for the day of the week alongside the hours of operation of the business.

14. The non-transitory machine readable medium of claim 13, wherein at least one of the plurality of data items that is indicative of the user request for interaction comprises a telephone call to the business that was initiated by a user, or an indication that the user was at a location of the business.

15. The non-transitory machine readable medium of claim 13, wherein at least one of the plurality of data items that is indicative of the user interaction with the business comprises a credit card transaction conducted by the business or an offer processed by the business.

16. The non-transitory machine readable medium of claim 13, wherein each of the plurality of data items is indicative of the user interaction with the business, the time of the day of the week associated with each of the plurality of data items is within a subset of the hours of operation, and the determined modified hours of operation comprises the subset of the hours of operation.