US-12625913-B2 - On-line system and method for searching recipes for meal planning

US12625913B2US 12625913 B2US12625913 B2US 12625913B2US-12625913-B2

Abstract

Embodiments relate to a system and method to plan preparation of a meal that may include more than one dish. Online recipes are obtained from a database based on criteria set by the user. Recipes are analyzed for time and effort requirements at each step. If a meal includes more than one dish, a merge of the timelines is performed to determine if it is feasible to prepare all dishes concurrently. Suppliers that can supply all ingredients required by the recipes that meet all user criteria are recommended to the user.

Inventors

Chris Knight

Assignees

7262591 CANADA LTD.

Dates

Publication Date: 20260512
Application Date: 20241209

Claims (9)

1 . A method for searching and managing recipes for meal planning, the method comprising: searching one or more recipe databases in accordance with a search request that includes a first user-defined criteria; displaying, on a user interface, in response to the search request, a search output, the search output comprising one or more recipes; receiving, from the user interface, a planning request based on a second user-defined criteria, the planning request including at least one recipe from the one or more recipes; performing, in response to the planning request, a step start and stop time analysis of individual preparation steps of the at least one recipe; merging step start and stop times obtained from the step start and stop time analysis for preparing the at least one recipe to generate a consolidated recipe; and displaying an output based on the consolidated recipe, the output including a time chart for preparing the consolidated recipe, the time chart including a number of people required for each step of the consolidated recipe; wherein the step start and stop time analysis further comprises: obtaining, for the at least one recipe, one or more training recipes from the one or more recipe databases; and performing a plurality of operations, the operations configured to: use the training recipes to identify and infer tasks or blocks of tasks of the consolidated recipe; and use the training recipes to identify and infer a time gap between the tasks or blocks of tasks of the consolidated recipe, wherein during the time gap zero people are required to perform one of the tasks or blocks of tasks; wherein the training recipes are further used to extend the time gap to insert one or more parallel tasks to optimize the consolidated recipe.
2 . The method of claim 1 , wherein searching the one or more recipe databases includes searching an ingredient supplier database, a recipe database, and a calorie database.
3 . The method of claim 1 , further comprising providing a list of ingredient suppliers.
4 . The method of claim 1 , further comprising providing a total cost of ingredients.
5 . The method of claim 1 , further comprising modifying the at least one recipe based on a number of servings required.
6 . The method of claim 1 , further comprising comparing an ingredient list for each recipe of the at least one recipe with ingredients in a user pantry to generate a shopping list for missing ingredients.
7 . The method of claim 1 , wherein the method includes a website based method or an app based method.
8 . The method of claim 1 , wherein the tasks or blocks of tasks of the consolidated recipe are performed intermittently.
9 . The method of claim 1 , wherein the time gap includes a precise time gap or a flexible time gap.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS The present application claims the filing benefit of co-pending U.S. application Ser. No. 18/216,796, filed on Jun. 30, 2023 claiming the filing benefit of U.S. application Ser. No. 17/258,814, filed on Jan. 8, 2021 claiming the filing benefit of Intl. Application No. PCT/CA2019/050851, filed Jun. 17, 2019 claiming the filing benefit of U.S. Application No. 62/695,257, filed Jul. 9, 2018, the disclosures of which are incorporated by reference herein in their entireties. FIELD OF INVENTION The disclosure relates generally to natural language processing and machine learning. More specifically, embodiments provide techniques to plan the preparation of a meal by applying text analytics and machine learning approaches to online recipes. BACKGROUND A recipe usually includes multiple steps, some of which require active involvement from the recipe user and others require no or minimal attention from the recipe user. Frequently a recipe user is looking to prepare a meal of several dishes (e.g. an appetizer, a main course, and dessert) within a specific time period (e.g. a maximum of 6 hours). While many recipes provide total preparation time and total cooking time, they do not indicate the timeline of the individual steps. When a user selects potential recipes to prepare for a meal, he will need to determine if it is feasible to prepare all the dishes concurrently and within the desired time frame, based on the description of the steps. If it is not feasible, the user will have to substitute one or more of the potential recipes and carry out the analysis all over again. For users with limited experience or practice in meal preparation, such an exercise could be daunting. Recipes are typically unstructured text. A particular task can be described in different ways. Furthermore, the time required for each task may not be stated and needs to be inferred. For example, one of the steps of a roasted vegetables recipe involves chopping of 4 different vegetables into pieces. An experienced user would estimate washing and chopping of the vegetables will take 30 minutes. Such time estimation is not usually stated explicitly in a recipe. This background information is provided for the purpose of making known information believed by the applicant to be of possible relevance to the present invention. No admission is necessarily intended, nor should be construed, that any of the preceding information constitutes prior art against the present invention. SUMMARY OF THE INVENTION An object of the present invention is to provide an on-line system and method for searching recipes for meal planning. In accordance with an aspect of the present invention, there is provided an on-line system for searching recipes for meal planning, the system comprising a memory that stores program code, a processor that executes the program code to: search an online recipe database based on user-defined criteria; perform timeline analysis of preparation steps; merge timelines to allow the user to prepare all dishes concurrently; and generate output to provide the user with a time chart to prepare all desired dishes concurrently. In some embodiments, the system comprises program code to infer level of involvement required from the user at each step using text analytics and machine learning approaches. In some embodiments, the system comprises program code to search ingredient supplier databases. In some embodiments, the system comprises program code to provide a list of ingredient suppliers. In some embodiments, the system comprises program code to provide a total cost of ingredients. In some embodiments, the system comprises program code to modify each recipe of the meal plan based on number of servings required. In some embodiments, the system comprises program code to compare ingredient list for each recipe of the meal plan and ingredients user has in their pantry to generate a shopping list for any missing ingredients. Optionally, the shopping list may include supplier information for each ingredient. In accordance with another aspect of the invention, there is provided a computer implemented method for searching recipes for meal planning, the method comprising searching an online recipe database based on user-defined criteria; performing timeline analysis of preparation steps; merging timelines to allow the user to prepare all dishes concurrently; and generating output to provide the user with a time chart to prepare all desired dishes concurrently. In some embodiments, the method comprises inferring the number of people required to perform each consolidated recipe step using text analytics and machine learning approaches. In some embodiments, the method comprises searching ingredient supplier databases. In some embodiments, the method comprises providing a list of ingredient suppliers. In some embodiments, the method comprises providing a total cost of ingredients. In some embodiments, the method comprises mod