Method for Passive Mining of Usage Information In A Location-Based Services System

• US 20150269619A1
• Filed: 06/05/2015
• Published: 09/24/2015
• Est. Priority Date: 04/27/2001
• Status: Abandoned Application

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Gailey, Michael L., Portman, Eric A., Burgiss, Michael J., Holmes, Chad S., King Smith, Angela
• Application Number:
  US14/732,549
• Publication Number:
  US 20150269619A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0256 User search
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0264 based upon schedule
• CPC Class Codes: G06Q 30/0267 Wireless devices
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0625 Directed, with specific intent or strategy
• CPC Class Codes: G06Q 30/0633 Lists, e.g. purchase orders, compilation or processing
• CPC Class Codes: G06Q 30/0639 Item locations
• CPC Class Codes: G06Q 50/12 Hotels or restaurants
• CPC Class Codes: G10L 15/1822 Parsing for meaning understanding
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 15/30 Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
• CPC Class Codes: G10L 2015/228 of application context
• CPC Class Codes: H04L 67/04 : specially adapted for terminals or networks with limited capabilities; specially adapted for terminal portability
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04L 67/52 : specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/53 : using third party service providers
• CPC Class Codes: H04M 2201/40 : using speech recognition speech recognition per se G10L15/00
• CPC Class Codes: H04M 2207/18 : wireless networks
• CPC Class Codes: H04M 2242/15 : Information service where the information is dependent on the location of the subscriber
• CPC Class Codes: H04M 2242/30 : Determination of the location of a subscriber
• CPC Class Codes: H04M 3/42204 : Arrangements at the exchange for service or number selection by voice at the terminal H04M1/27
• CPC Class Codes: H04M 3/42348 : Location-based services which utilize the location information of a target
• CPC Class Codes: H04M 3/4936 : Speech interaction details speech recognition per se G10L15/00
• CPC Class Codes: H04W 4/023 : using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 4/23 : for mobile advertising

Abstract

A method and system for providing advertising effectiveness searching capabilities, predictive modeling capabilities and usage mining in a location-based services system is disclosed. During operation of the location-based services system, usage information for advertising campaigns placed on the location-based services system is stored. Advertisers are provided with the ability to enter a search request form on a remote terminal to mine the usage information. The search request is then transmitted to an application that searches usage information to generate a response to said search request.

Claims

1-6. -6. (canceled)

7. A computer-implemented method comprising:

receiving, at a computer system and from a first client computing device, a first request for the computer system to host first product information and first restaurant information for a first group of restaurants;

storing, by the computer system, the first product information and the first restaurant information in association with the first group of restaurants, wherein the first product information identifies, at least, first products offered by the first group of restaurants, wherein the first restaurant information identifies, at least, first locations of restaurants in the first group of restaurants;

receiving, at the computer system and from a second client computing device, a second request for the computer system to host second product information and second restaurant information for a second group of restaurants, wherein the first group of restaurants is different from the second group of restaurants;

storing, by the computer system, the second product information and the second restaurant information in association with the second group of restaurants, wherein the second product information identifies, at least, second products offered by the second group of restaurants, wherein the second restaurant information identifies, at least, second locations of restaurants in the second group of restaurants;

receiving, at the computer system and from a mobile computing device, a request for a product, wherein the request includes information that identifies the product and a location of the mobile computing device;

selecting, by the computer system, a particular restaurant to use for the request based, at least in part, on (i) the product identified in the request, (ii) the location of the mobile computing device, (iii) the first product information and the first restaurant information stored by the computer system, and (iv) the second product information and the second restaurant information stored by the computer system; and

using, by the computer system, the particular restaurant to process the request from the mobile computing device.

8. The computer-implemented method of claim 7, wherein:

the first restaurant information further includes first hours information identifying first hours of operation for the first group of restaurants,

the second restaurant information further includes second hours information identifying second hours of operation for the second group of restaurants,

storing further includes storing the first hours information in association with the first group of restaurants and storing the second hours information in association with the second group of restaurants, and

the particular restaurant is selected further based, at least in part, on the first hour information and the second hours information.

9. The computer-implemented method of claim 7, wherein:

the first restaurant information further includes first product offering information identifying which of the first products are offered at each of the first group of restaurants,

the second restaurant information further includes second product offering information identifying which of the second products are offered at each of the second group of restaurants,

storing further includes storing the first product offering information in association with the first group of restaurants and storing the second product offering information in association with the second group of restaurants, and

the particular restaurant is selected further based, at least in part, on the first product offering information and the second product offering information.

10. The computer-implemented method of claim 7, wherein:

the first product information further includes first product price information identifying first prices for the first products that are offered at the first group of restaurants,

the second product information further includes second product price information identifying second prices for the second products that are offered at the second group of restaurants,

storing further includes storing the first product price information in association with the first group of restaurants and storing the second product price information in association with the second group of restaurants, and

the particular restaurant is selected further based, at least in part, on the first product price information and the second product price information.

11. The computer-implemented method of claim 7, wherein:

the first restaurant information further includes first discount information identifying first discounts that are being offered at the first group of restaurants,

the second restaurant information further includes second discount information identifying second discounts that are being offered at the second group of restaurants,

storing further includes storing the first discount information in association with the first group of restaurants and storing the second discount information in association with the second group of restaurants, and

the particular restaurant is selected further based, at least in part, on the first discount information and the second discount information.

12. The computer-implemented method of claim 7, wherein:

the request from the mobile computing device further includes information designating the first group of restaurants for the request, and

the particular restaurant is selected further based, at least in part, on the designation of the first group of restaurants for the request.

13. The computer-implemented method of claim 12, wherein the particular restaurant is selected based on, from among the first locations of restaurants in the first group of restaurants, the particular restaurant having a location that is closest to the location for the mobile computing device.

14. The computer-implemented method of claim 7, wherein:

the first group of restaurants comprises a first restaurant chain with restaurants at the first locations, and

the second group of restaurants comprises a second restaurant chain with restaurants at the second locations.

15. The computer-implemented method of claim 7, further comprising:

logging, by the computer system, usage information for use of the particular restaurant to process the request, wherein the usage information is logged in association with either the first group of restaurants or the second group of restaurants based on whether the particular restaurant is a member of the first group of restaurants or the second group of restaurants;

providing, by the computer system, the first computing device with first access to the stored usage information, the first access being restricted to portions of the stored usage information that is associated with the first group of restaurants; and

providing, by the computer system, the second computing device with second access to the stored usage information, the second access being restricted to portions of the stored usage information that is associated with the first group of restaurants.

16. The computer-implemented method of claim 7, wherein:

the first request additionally requests that the first product information and first restaurant information be hosted by the computer system as push content to be pushed to mobile computing devices by a push service of the computer system,

the first product information and the first restaurant information are stored with a designation as push content;

the method further comprising;

receiving, at the computer system, location information indicating that a another mobile computing device is at a particular location;

accessing, by the computer system and in response to receiving the location information, push subscription information for the other mobile computing device that indicates user consent to receive push notifications on the other mobile computing device;

determining, by the computer system and in response to accessing the push subscription information, whether to send a push notification to the other mobile computing device based, at least in part, on a comparison of the particular location of the other mobile computing device and the first locations of restaurants in the first group of restaurants identified in the first restaurant information; and

providing, by the computer system based on the determining, a push notification to the other mobile computing device that includes information from one or more of the first product information and the first restaurant information.

17. A computer system comprising:

one or more restaurant interfaces that are programmed to receive requests, from computing devices associated with restaurants, to host product information and restaurant information for a plurality of groups of restaurants;

one or more data storage devices that are programmed to store the product information and the restaurant information for the plurality of groups of restaurants, wherein the product information identifies, at least, products offered by the each of the plurality of groups of restaurants, wherein the restaurant information identifies, at least, locations of restaurants in each of the plurality of groups of restaurants;

one or more mobile device interfaces that are programmed to receive requests for products from mobile computing devices, wherein the requests includes information that identifies the products and locations of the mobile computing devices; and

a location-based request subsystem that is programmed to (i) select a particular restaurant to use for each of the requests based, at least in part, on the products identified in the requests, the locations of the mobile computing devices, the stored product information, and the stored restaurant information, and (ii) use the particular restaurants to process the requests from the mobile computing devices.

18. The computer system of claim 17, wherein:

the restaurant information further includes hours information identifying hours of operation for the plurality of groups of restaurants,

the data storage devices are further programmed to store the hours information, and

the location-based request subsystem is further programmed to select the particular restaurants additionally based on the hours information.

19. The computer system of claim 17, wherein:

the restaurant information further includes product offering information identifying which of the products are offered at each of the plurality of groups of restaurants,

the data storage devices are further programmed to store the product offering information, and

the location-based request subsystem is further programmed to select the particular restaurants additionally based on the product offering information.

20. The computer system of claim 17, wherein:

the product information further includes product price information identifying prices for the products that are offered at each of the plurality of groups of restaurants,

the data storage devices are further programmed to store the product price information, and

the location-based request subsystem is further programmed to select the particular restaurants additionally based on the product price information.

21. The computer system of claim 17, wherein:

the restaurant information further includes discount information identifying discounts that are being offered at the each of the plurality of groups of restaurants,

the data storage devices are further programmed to store the discount information, and

the location-based request subsystem is further programmed to select the particular restaurants additionally based on the discount information.

22. The computer system of claim 17, wherein:

the requests from the mobile computing devices further include information designating a particular group of restaurants from the plurality of groups of restaurants, and

the particular restaurant is selected further based, at least in part, on the designation of the particular group of restaurants for the requests.

23. The computer system of claim 22, wherein the particular restaurant is selected based on, from among the particular group of restaurants, the particular restaurant having a location that is closest to the locations for the mobile computing devices.

24. The computer system of claim 17, wherein each of the plurality of groups of restaurants comprises a restaurant chain with a plurality of restaurants.

25. The computer system of claim 17, wherein:

the data storage devices are further programmed to log usage information related to use of the particular restaurants to process the requests, wherein the usage information is logged in association with corresponding groups from the plurality of groups of restaurants, and

the restaurant interfaces are further programmed to provide the computing devices associated with restaurants with access to the stored usage information in a manner that restricts access to only those portions of the stored usage information that are associated with groups of restaurants that are associated with the computing devices.

26. The computer system of claim 17, wherein:

the one or more restaurant interfaces is further programmed to receive location information from mobile computing devices that indicate the locations of the mobile computing devices,

the data storage devices are further programmed to store (i) the product information and the restaurant information with designations as push content, and (ii) push subscription information for the mobile computing devices that indicate user consent to receive push notifications on the mobile computing devices, and

the location-based request subsystem is further programmed to send push notifications to the mobile computing devices in response to (i) receiving the location information, (ii) identifying that user associated with the mobile computing devices have consented to receive push notification, and (iii) determining that criteria for sending the push notifications have been satisfied based, at least in part, on a comparison of the location information for the mobile computing devices and the locations of restaurants in each of the plurality of groups of restaurants.