Intelligent menu recommendation method, household appliance and computer-readable storage medium

Abstract

A smart menu recommendation method, household appliance and computer-readable storage medium. The method includes presetting label information of menus in a menu database, wherein the menu database includes menus frequently used by users, and the label information is used to indicate the characteristics of the menus; when a user accesses a menu carrying the label information, the label information is marked; according to the number of times the label information is marked, a first target menu list is formed, and the first target menu list is displayed to the user. The above scheme can be used to recommend menus to users based on the number of times the label corresponding to the user's accessed menu is marked, thereby achieving the effect of intelligent recommendation and improving the user's experience. At the same time, the user's dietary preferences can be fully considered.

Description

Technical Field

[0001] The present invention relates to the technical field of household appliances, and in particular to an intelligent method for menu recommendation, a household appliance and a computer-readable storage medium. Background Art

[0002] There are many solutions for food or menu recommendations on household appliances, especially refrigerators. Existing solutions include making food recommendations based on the user's health status, dietary preferences, etc. However, there is a situation where the refrigerator lacks the corresponding ingredients for the recommended menu, resulting in the user being unable to experience the convenience brought by the recommended diet. Therefore, existing solutions have not yet achieved intelligent and localized dietary recommendations. Summary of the invention

[0003] An object of an embodiment of the present invention is to provide an improved method for recommending intelligent recipes.

[0004] One purpose of an embodiment of the present invention is to prioritize menus according to the number of times menu labels in a home appliance are identified, thereby intelligently recommending menus.

[0005] A smart menu recommendation method, which can be applied to a household appliance, wherein the household appliance is used to store ingredients and preset label information of menus in a menu database, wherein the menu database includes menus frequently used by users, and the label information is used to indicate the characteristics of the recipes; when a user accesses a menu carrying the label information, the label information is marked; according to the number of times the label information is marked, a first target menu list is formed, and the first target menu list is displayed to the user.

[0006] In a possible embodiment, presetting the label information of the menu in the menu database includes: receiving the label information of the corresponding menu, and establishing a correspondence between the label information and the menu.

[0007] In a possible embodiment, if the first target menu list includes at least two menus with the same number of marks, the menus with the same number of marks are sorted according to the food inventory list in the home appliance to form a second target menu list.

[0008] In a possible embodiment, sorting the menus with the same number of markings according to the ingredient inventory list in the household appliance includes determining the number of ingredient types required for each menu in the menus with the same number of markings according to the ingredient inventory list; and sorting the corresponding menus according to the number of ingredient types to form a second target menu list.

[0009] In a possible embodiment, the method further includes performing deduplication calculation on menus in the first and / or second target menu lists.

[0010] In a possible embodiment, displaying the first target menu list to the user includes presetting a menu threshold of the first target menu list, and displaying the first target menu list within the preset threshold range to the user through a screen of a mobile device or a home appliance.

[0011] In a possible embodiment, the household appliance includes a refrigerator.

[0012] An intelligent menu recommendation device includes: an acquisition module for presetting label information of menus in a menu database, wherein the menu database includes menus frequently used by users, and the label information is used to indicate the characteristics of the recipes; a first processing module for marking the label information when the user accesses a menu carrying the label information; and a second processing module for forming a first target menu list according to the number of times the label information is marked, and displaying the first target menu list to the user.

[0013] In a possible embodiment, the acquisition module is further used to receive label information corresponding to the menu, and establish a corresponding relationship between the label information and the menu.

[0014] In a possible embodiment, the device further includes a third processing module for sorting the menus with the same number of marks according to an ingredient inventory list in the household appliance to form a second target menu list if at least two menus with the same number of marks are included in the first target menu list.

[0015] In a possible embodiment, the third processing module is further used to determine the number of ingredient types required for each menu among menus with the same number of markings based on the ingredient inventory list; sort the corresponding menus according to the number of ingredient types to form a second target menu list.

[0016] In a possible embodiment, the device further includes a deduplication module, configured to perform deduplication calculation on menus in the first and / or second menu lists.

[0017] In a possible embodiment, the second processing module is further used to preset a menu threshold of the first target menu list, and display the first target menu list within the preset threshold range to the user through the screen of the mobile device or the home appliance.

[0018] A household appliance comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the aforementioned intelligent menu recommendation method when executed by the processor.

[0019] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the aforementioned intelligent menu recommendation method are implemented.

[0020] Compared with the prior art, the technical solution of the present invention has the following advantages:

[0021] The above solution can be used to recommend menus to users based on the number of times the label corresponding to the menu accessed by the user is identified, thereby achieving the effect of intelligent recommendation and improving the user experience. At the same time, the user's dietary preferences can be fully considered. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a flow chart of an intelligent menu recommendation method in an embodiment of the present invention;

[0023] Figure 2 is a block diagram of a household appliance in an embodiment of the present invention;

[0024] Figure 3 It is a structural block diagram of the intelligent menu recommendation device in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] like Figure 1 , discloses an intelligent menu recommendation method, which can be applied to household appliances, where the household appliances are used to store food, such as refrigerators, freezers, etc. The method comprises:

[0026] S100 presets label information of menus in a menu database, wherein the menu database includes menus frequently used by users, and the label information is used to indicate features of recipes; wherein the menu database includes information on ingredients, cooking steps, and the like.

[0027] S102: when the user accesses a menu carrying the tag information, marking the tag information;

[0028] S104: forming a first target menu list according to the number of times the tag information is marked, and displaying the first target menu list to the user.

[0029] The method can recommend menus to users based on the number of times the label corresponding to the menu accessed by the user is identified, thereby achieving the effect of intelligent recommendation and improving the user experience. At the same time, the user's dietary preferences can be fully considered.

[0030] In one embodiment, step S100 can be preset by the user. The label information of the corresponding menu can be received, and the label information and the menu can be correspondingly related. In this way, each menu has corresponding label information, for example, fried tomato and eggs correspond to the label "sweet and sour", and mapo tofu corresponds to the label "spicy". Of course, different menus can have the same label. For example, user-defined labels can be pre-defined, or preference labels can be defined for the user in the user's menu access history. For example, if the menu accessed by the user has a label "baking", the label "baking" is marked, and the more marked labels are, the closer they are to the user's real preferences.

[0031] In one embodiment, when a menu is accessed, the label corresponding to the menu is identified, and the number of identifications can be accumulated by counting. Then, according to the number of times the label is identified, the corresponding menus can be arranged in reverse order to form a menu list, which is called the first target menu list. In one embodiment, the menu is searched in the menu database, and the label corresponding to each searched menu is marked. For example, in the menu A position, where menu A corresponds to label a, label a is marked once, and menu B also corresponds to label a, which is marked again once. After multiple visits by the user, the number of menu label marks is sorted in reverse order. The menu corresponding to the label that has been marked the most times reflects the user's preference and is presented first.

[0032] In one embodiment, if the first target menu list includes at least two menus with the same number of marks, the menus with the same number of marks may be sorted again according to the food inventory list in the home appliance to form a second target menu list. The menu with a larger number of marks may be presented first.

[0033] In one embodiment, the number of ingredient types required for each menu in the menus with the same number of markings can be determined based on the ingredient inventory list; then the corresponding menus can be sorted according to the number of ingredient types to form a second target menu list.

[0034] For example, in the first target menu list, menu A labeled "sweet and sour" and menu B labeled "spicy" have the same number of representations, so a secondary sort can be performed by judging the number of types of ingredients required for each menu. The aforementioned household appliance is a refrigerator, and the existing ingredients in the refrigerator include tomatoes, eggs, potatoes, and carrots. The system judges based on the existing inventory that menu B uses three ingredients, tomatoes, potatoes, and carrots; menu A uses two ingredients, tomatoes and eggs. Therefore, menu B has a higher priority than menu A. In one embodiment, the above method also includes deduplication calculations for menus in the first or second menu list. The menus recommended according to the above method may be repeated. For example, if the user's refrigerator inventory contains tomatoes and eggs, the menu recommended in the front may be the same dish "Tomato Scrambled Eggs" from different data sources or different menu authors.

[0035] In order to ensure the diversity of recommendations, the system can perform deduplication processing on the menus finally presented to users, remove menus with the same title, and retain menus that are officially certified / have a high number of visits. The advantage is that it can put the highest priority information in front according to the user's inventory and preferences, avoiding manual search by users and helping users save time and energy. At the same time, it maximizes the use of the customer's inventory of ingredients, avoids unnecessary waste, and allows customers to eat diversified food and get more nutrition.

[0036] In one embodiment, a menu threshold of the first target menu list can be preset, and the first target menu list within the preset threshold range can be displayed to the user through the screen of the mobile device or the home appliance. For example, if the system stipulates that the number of menus presented to the user at a time is ten items, then after obtaining the first target menu list, the first ten menus with descending priorities are displayed to the user.

[0037] like Figure 2 The embodiment of the present invention further discloses a household appliance 10, comprising: a memory 101, a processor 102, and a computer program stored in the memory 101 and executable on the processor 102, wherein the computer program implements steps S100, S102, and S104 of the aforementioned intelligent menu recommendation method when executed by the processor 102.

[0038] like Figure 3 The embodiment of the present invention discloses an intelligent menu recommendation device 20, comprising: an acquisition module 201, used to preset label information of menus in a menu database, wherein the menu database includes menus frequently used by users, and the label information is used to indicate the characteristics of the recipes; a first processing module 202, used to mark the label information when the user accesses a menu carrying the label information; a second processing module 203, used to form a first target menu list according to the number of times the label information is marked, and display the first target menu list to the user.

[0039] It can be understood that the acquisition module 201, the first processing module 202 and the second processing module 203 in this embodiment are respectively the execution subjects of the steps in the aforementioned method embodiment, and are respectively used to execute the corresponding method steps.

[0040] In one embodiment, the household appliance 10 includes an intelligent menu recommendation device 20 .

[0041] In one embodiment, the acquisition module 201 is further used to receive label information corresponding to the menu, and establish a correspondence between the label information and the menu.

[0042] In one embodiment, the intelligent menu recommendation device 20 also includes a third processing module 204, which is used to sort the menus with the same number of marks according to the ingredient inventory list in the household appliance to form a second target menu list if at least two menus with the same number of marks are included in the first target menu list.

[0043] In one embodiment, the third processing module 204 is further used to determine the number of ingredient types required for each menu among menus with the same number of markings according to the ingredient inventory list; sort the corresponding menus according to the number of ingredient types to form a second target menu list.

[0044] In one embodiment, the intelligent menu recommendation device 20 further includes a deduplication module 205 for performing deduplication calculation on the menus in the first or second menu list.

[0045] In one embodiment, the second processing module 203 is further used to preset a menu threshold of the first target menu list, and display the first target menu list within the preset threshold range to the user through the screen of the mobile device or home appliance.

[0046] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0047] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0048] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0049] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0050] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0051] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method of the embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0052] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An intelligent menu recommendation method, applied to a household appliance, wherein the household appliance is used to store food ingredients, characterized in that: The method comprises: presetting label information of menus related to food information in a menu database, wherein the menu database comprises menus frequently used by users, the menus at least comprising food information or cooking steps, and the label information is used to indicate the characteristics of the menus; When the user accesses a menu carrying the tag information, marking the tag information; According to the number of times the tag information is marked, a first target menu list is formed, wherein if the first target menu list includes at least two menus with the same number of marks, the number of ingredient types required for each of the menus with the same number of marks is determined according to the ingredient inventory list in the household appliance; the corresponding menus are sorted according to the number of ingredient types, and the re-sorted menu list is displayed to the user; Presetting the label information of the menu in the menu database includes: receiving the label information of the corresponding menu, and establishing a corresponding relationship between the label information and the menu.

2. The method according to claim 1, characterized in that The method also includes performing a deduplication calculation on the menus in the re-sorted menu list.

3. The method according to claim 1, characterized in that Displaying the re-sorted menu list to the user includes presetting a menu threshold of the menu list, and displaying the re-sorted menu list within the preset threshold range to the user through the screen of the mobile device or the home appliance.

4. The method according to claim 1, characterized in that The household appliance includes a refrigerator.

5. A household appliance comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the intelligent menu recommendation method according to any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the intelligent menu recommendation method according to any one of claims 1 to 4 are implemented.

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