Recipe suggestion apparatus and method

Patent metadata

Field	Value
Publication number	US-9536237-B2
Application number	US-201213688134-A
Country	US
Kind code	B2
Filing date	Nov 28, 2012
Priority date	Nov 28, 2012
Publication date	Jan 3, 2017
Grant date	Jan 3, 2017

Abstract

A computer-implemented method is disclosed for suggesting recipes. Within the method, one or more point-of-sale transactions may be conducted. The transactions may involve a computer system and a customer possessing a mobile computing device. The computer system may store receipt data documenting the transactions. The computer system may also receive a request from the mobile computing device for one or more recipes, analyze the receipt data to identify at least one of the food patterns and food preferences of the customer, and identify one or more recipes corresponding to at least one of the food patterns and food preferences. The computer system may then pass the one or more recipes to the mobile computing device.

First claim

What is claimed is:

1. A method for suggesting recipes, the method comprising:
providing a first computer system having an input device;
providing a second computer system in communication with the first computer system, the second computer system having a processor including an output module, an analysis module, and a control module;
providing a recipe database that stores a plurality of recipes;
receiving, through the first computer system, a plurality of sale transactions;
forwarding the plurality of sale transactions to the output module;
generating, through the analysis module, a user interface control, the user interface control representing a correlation scale of customer-adjustable experimentation settings, the correlation scale indicating the correlation of a recipe with each of a plurality of micro patterns and macro preferences of a customer, the micro patterns of the customer including sale transaction patterns for the customer, the macro preferences of the customer including categorized food types for the customer determined through analysis of the micro patterns;
providing an application executable by a mobile computing device in communication with the second computer system;
presenting, through the output module, the user interface control to the application, the user interface control representing the correlation scale, the correlation scale embodied as a slidable scale with each position on the slidable scale representing a different experimentation setting for the customer;
receiving, through the control module, a selection of one of the experimentation settings by the customer selecting one of the positions on the slidable scale;
receiving, through the control module, a request for one or more recipes from the mobile computing device;
analyzing, through the analysis module, the one or more sale transactions of the customer to identify each of the micro patterns of the customer and macro preferences of the customer;
identifying a food item within the one or more sale transactions;
determining, through the analysis module, a statistical significance of the food item with respect to the one or more sale transactions;
correlating, by the analysis module, the food item with at least one of the micro patterns or at least one of the macro preferences of the customer upon a determination that the statistical significance of the food item exceeds a predetermined threshold;
omitting, by the analysis module, the food item from the one or more micro patterns and the one or more macro preferences upon a determination that the statistical significance of the food item does not exceed the predetermined threshold;
indicating, through the analysis module, a correlation between a recipe and each of the micro patterns of the customer and macro preferences of the customer for the recipe to be identified as potentially relevant to the customer;
identifying, through the analysis module, one or more of the plurality of recipes from within the recipe database as being potentially relevant to the customer, each of the one or more recipes corresponding to the correlation a recipe is to have with each of: micro patterns of the customer, macro preferences of the customer, and the customer-selected experimentation setting;
associating at least one photograph with the one or more identified recipes; and
transmitting, through the output module, the one or more identified recipes and the at least one associated photograph to the mobile computing device.

2. The method of claim 1 , wherein the first computer system comprises a plurality of first computer systems housed within one or more retail, brick-and-mortar stores corresponding to a retailer.

3. The method of claim 2 , further comprising conducting the one or more sale transactions at one or more first computer systems of the plurality of first computer systems.

4. The method of claim 3 , wherein the one or more recipes are product-specific recipes.

5. The method of claim 3 , wherein the one or more recipes are product-independent recipes.

6. The method of claim 5 , further comprising obtaining the recipe database from an entity independent of the retailer.

7. The method of claim 5 , further comprising receiving, through a synchronization module within the processor, a request from the mobile computing device to convert a first recipe of the one or more recipes into a product-specific recipe.

8. The method of claim 7 , further comprising applying, through the conversion module, fuzzy logic to the first recipe and converting, through the conversion module, the first recipe into a product-specific recipe.

9. The method of claim 8 , further comprising passing, through the output module, the product-specific recipe to the mobile computing device in the form of a shopping list or a modification to a shopping list.

10. The method of claim 1 , wherein identifying one or more recipes from within the recipe database comprises identifying one or more recipes corresponding to both the purchase patterns and cuisine preferences.

11. The method of claim 1 , wherein the identifying one or more recipes from within a recipe database comprises identifying one or more recipes corresponding to cuisine preferences that do not correspond to the purchase patterns.

12. A computer program product for use with a first computer system and a second computer system in communication with the first computer system configured for implementing a method for suggesting recipes, the first computer having an input device and the second computer having a processor, the computer program product comprising:
one or more computer storage devices having stored thereon computer-executable instructions that, when executed on the processor including a control module, an analysis module, and an output module, cause the processor to perform a method including the following:
storing a plurality of recipes in a recipe database;
receiving, through the first computer system, a plurality of sale transactions;
forwarding the plurality of sale transactions to the output module;
generating, through the analysis module, a user interface control, the user interface control representing a correlation scale of customer-adjustable experimentation settings, the correlation scale indicating the correlation of a recipe with each of a plurality of micro patterns and macro preferences of a customer, the micro patterns of the customer including sale transaction patterns for the customer, the macro preferences of the customer including categorized food types for the customer determined through analysis of the micro, food items in the micro patterns having been analyzed to determine the macro preferences;
providing an application executable by a mobile computing device in communication with the second computer system;
presenting, through the output module, the user interface control to the application, the user interface control representing the correlation scale, the correlation scale embodied as a slidable scale with each position on the slidable scale representing a different experimentation setting for the customer;
receiving, through the control module, a selection of one of the experimentation settings by the customer selecting one of the positions on the slidable scale;
receiving, through the control module, a request for one or more recipes from the mobile computing device;
analyzing, through the analysis module, receipt data for one or more point-of-sale transactions of the customer to identify each of: micro patterns of the customer and macro preferences of the customer, the macro preferences of the customer including categorized food types for the customer determined t

Assignees

• Wal Mart Stores Inc

Inventors

• Argue Stuart
• Marcar Anthony Emile

Classifications

• G06Q30/0631

  Recommending goods or services · CPC title

• G06Q20/20 Primary

  Point-of-sale [POS] network systems · CPC title

• G06Q20/202

  Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR · CPC title

• G06Q30/0633 Primary

  Managing shopping lists, e.g. compiling or processing purchase lists (shipping orders G06Q10/083; order filling G06Q10/087) · CPC title