Dish recommendation method and electronic equipment

Abstract

The invention provides a dish recommendation method and electronic equipment. The method comprises the following steps: displaying a dish recommendation control on a page corresponding to a target store, wherein the target store is displayed in a merchant applet or a life service e-commerce platform application; receiving a dining demand input by the user through the dish recommendation control, wherein the dining demand at least comprises the dish taste, the number of people and the price; a dish recommendation list formed according to the dining demand is displayed, the dish recommendation list comprises at least one dish corresponding to the target shop, and the dish recommendation list displays the dishes in a partitioned mode according to the dish types; in response to a selection operation or an input operation of a user on the dish recommendation control, sending the changed dining demand to artificial intelligence, updating the dish recommendation list through the artificial intelligence, and displaying the updated dish recommendation list; and responding to a preset settlement operation of the user on the dish recommendation control, and forming a user order according to the dish recommendation list. According to the embodiment of the invention, the dish ordering efficiency of the user can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence technology, and more specifically, to a dish recommendation method and electronic device. Background Art

[0002] When ordering food, users typically need to consider factors such as which restaurant to choose, which dishes to choose, the taste, and the average price per person. Related technologies typically use review apps or group buying apps to provide recommended restaurants based on the user's location. The corresponding store pages provide links to various group buying packages and display several recommended dishes from the store to improve user ordering efficiency.

[0003] However, users still need to click into each group purchase package to view the specific dishes and find a suitable package. If there is a suitable package, they can purchase it and find a waiter to redeem the group purchase voucher. If there is no suitable package, they also need to ask the waiter on the spot about the various dishes, or scan the code to order by themselves to find the right dishes among the massive number of dishes.

[0004] This way of ordering food is still time-consuming, labor-intensive and inefficient.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0006] The purpose of the present disclosure is to provide a dish recommendation method and electronic device for improving the efficiency of user ordering.

[0007] According to a first aspect of an embodiment of the present disclosure, a dish recommendation method is provided, including: displaying a dish recommendation control on a page corresponding to a target store, the target store being displayed in a merchant mini-program or in an application of a life service e-commerce platform; receiving dining needs input by a user through the dish recommendation control, the dining needs at least including dish taste, number of people, and price, the dining needs being used to generate a dish recommendation list through artificial intelligence; displaying a dish recommendation list formed according to the dining needs, the dish recommendation list including at least one dish corresponding to the target store, the dish recommendation list displaying the dishes according to dish category; in response to a user's selection operation or input operation on the dish recommendation control, sending the changed dining needs to the artificial intelligence, updating the dish recommendation list through the artificial intelligence, and displaying the updated dish recommendation list; in response to a user's preset settlement operation on the dish recommendation control, forming a user order according to the dish recommendation list.

[0008] According to a second aspect of the present disclosure, an electronic device is provided, comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute any one of the above methods based on instructions stored in the memory.

[0009] The disclosed embodiment receives the user's dining needs by displaying a dish recommendation control on the page of the target store, and then automatically and intelligently forms a dish recommendation list corresponding to the target store based on the user's dining needs. The dish recommendation control and the dish recommendation list are displayed at the same time, allowing the user to adjust the dish recommendation list through the dish recommendation control and automatically form an order, which can help the user quickly form a dish order for the target store and greatly improve the user's ordering efficiency.

[0010] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0012] Figure 1 4 is a flowchart of a dish recommendation method in an exemplary embodiment of the present disclosure.

[0013] Figure 2A and Figure 2B It is a schematic diagram showing a dish recommendation control in an exemplary embodiment of the present disclosure.

[0014] Figure 3 2 is a schematic diagram of expanding a dish recommendation control in an exemplary embodiment of the present disclosure.

[0015] Figure 4A and Figure 4B 2 is a schematic diagram of inputting dining requirements in an exemplary embodiment of the present disclosure.

[0016] Figure 5 It is a sub-flowchart for forming a dish recommendation list in an exemplary embodiment of the present disclosure.

[0017] Figure 6A and Figure 6B is a schematic diagram of a waiting interface in an exemplary embodiment of the present disclosure.

[0018] Figure 7 2 is a schematic diagram of a dish recommendation list in an exemplary embodiment of the present disclosure.

[0019] Figures 8A to 8D 3 is a schematic diagram of adjusting a menu recommendation list by inputting dining requirements in an exemplary embodiment of the present disclosure.

[0020] Figure 9 2 is a schematic diagram of a selection control for recommending dishes in an exemplary embodiment of the present disclosure.

[0021] Figure 10 2 is a schematic diagram of an adjusted dish recommendation list in an exemplary embodiment of the present disclosure.

[0022] Figure 11 It is a schematic diagram of adjusting the display of a dish recommendation list and a dish recommendation control in an exemplary embodiment of the present disclosure.

[0023] Figures 12A to 12C 2 is a schematic diagram of accessing a dish recommendation control through a virtual shopping cart in an exemplary embodiment of the present disclosure.

[0024] Figure 13 It is a sub-flow chart of forming a user order in an exemplary embodiment of the present disclosure.

[0025] Figure 14 2 is a schematic diagram of an order confirmation page in an exemplary embodiment of the present disclosure.

[0026] Figure 15 is a block diagram of an electronic device in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present disclosure will be more comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or that other methods, components, devices, steps, etc. may be employed. In other cases, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0028] The accompanying drawings are merely schematic illustrations of the present disclosure. Identical reference numerals in the drawings denote identical or similar components, and thus their repeated descriptions will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0029] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0030] Figure 1 4 is a flowchart of a dish recommendation method in an exemplary embodiment of the present disclosure.

[0031] refer to Figure 1 The dish recommendation method 100 may include:

[0032] Step S1: Display a dish recommendation control on a page corresponding to a target store, wherein the target store is displayed in a merchant mini-program or in an application on a life service e-commerce platform;

[0033] Step S2: receiving dining requirements input by the user through the dish recommendation control, wherein the dining requirements include at least dish taste, number of people, and price range, and the dining requirements are used to generate a dish recommendation list through artificial intelligence;

[0034] Step S3, displaying a dish recommendation list formed according to the dining demand, wherein the dish recommendation list includes at least one dish corresponding to the target store, and the dish recommendation list displays the dishes by category;

[0035] Step S4, in response to the user's selection operation or input operation on the dish recommendation control, sending the modified dining requirements to the artificial intelligence, updating the dish recommendation list through the artificial intelligence, and displaying the updated dish recommendation list;

[0036] Step S5, responding to the user's preset settlement operation on the dish recommendation control, forming a user order according to the dish recommendation list.

[0037] The disclosed embodiment receives the user's dining needs by displaying a dish recommendation control on the page of the target store, and then automatically and intelligently forms a dish recommendation list corresponding to the target store based on the user's dining needs. The dish recommendation control and the dish recommendation list are displayed at the same time, allowing the user to adjust the dish recommendation list through the dish recommendation control and automatically form an order, which can help the user quickly form a dish order for the target store and greatly improve the user's ordering efficiency.

[0038] The functions of the disclosed embodiment can be called out in a variety of scenarios. Below, an embodiment of each step of the dish recommendation method 100 is described in detail.

[0039] In step S1, a dish recommendation control is displayed on a page corresponding to a target store, and the target store is displayed in a merchant mini program or in an application of a life service e-commerce platform.

[0040] In some application scenarios, users can open the life service e-commerce platform application on their mobile terminal and enter the page corresponding to the target store by clicking on a recommended store, searching for a store and clicking on it. In addition, users can also enter the merchant mini program corresponding to the target store in the mini program provided by a third-party platform to access the page corresponding to the target store.

[0041] In an exemplary embodiment, a dish recommendation control may be displayed on a page corresponding to a target store, and a user may call up the dish recommendation control to expand the dish recommendation control and provide dining needs.

[0042] Figure 2A and Figure 2B It is a schematic diagram showing a dish recommendation control in an exemplary embodiment of the present disclosure.

[0043] refer to Figure 2A and Figure 2B , on the page 20 corresponding to the target store, a dish recommendation control 21 is displayed.

[0044] When the dish recommendation control 21 is not operated, it can be Figure 2A The abbreviated form shown here can avoid affecting the user's traditional ordering process through the page; it can also be Figure 2B The prompt form shown is to remind the user to use the dish recommendation function, and the prompt form is not limited to the digital human image (such as Figure 2B ), animation form, highlight form (such as setting the brightness of the normal page to be slightly darker), etc., as long as the dish recommendation control 21 can be highlighted.

[0045] At this time, the evoked operation includes but is not limited to clicking, sliding or other forms of operation on the dish recommendation control 21 to expand the dish recommendation control 21. Figure 2A and Figure 2B In , the call-up action can be set to click the "Help me click" button.

[0046] In other embodiments of the present disclosure, the dish recommendation control 21 may not be directly displayed on the page, but the user may be prompted (for example, through a pop-up window, a floating ball, etc.) to call out the dish recommendation control 21 in other ways. For example, the calling operation of the dish recommendation control 21 may be set to long press the page 20, double-click the page 20, slide (including left and right sliding and up and down sliding) the page 20, etc., so that the user can call out the dish recommendation control 21 on the page 20.

[0047] It should be noted that page 20 can be any page corresponding to the target store (including but not limited to the homepage, secondary page, virtual shopping cart page), or any page part (such as the top, middle, or bottom of a long page that needs to be slid and browsed), as long as the target store corresponding to page 20 can be determined.

[0048] Figure 3 2 is a schematic diagram of expanding a dish recommendation control in an exemplary embodiment of the present disclosure.

[0049] refer to Figure 3 Whether it is through operating the thumbnail dish recommendation control 21 or directly performing the call-up operation on page 20, the expanded form of the dish recommendation control 21 can be either full screen mode or as shown below. Figure 3 When the dish recommendation control 21 occupies part of the screen, the docking position can be the bottom of the screen (such as Figure 3 as shown), top, left, right or center.

[0050] The dish recommendation control 21 is a human-computer interaction control for receiving information input by the user. The user can input dining needs to the dish recommendation control 21 through various input methods such as text or voice.

[0051] In step S2, the dining requirements input by the user are received through the dish recommendation control, and the dining requirements at least include dish taste, number of people, and price. The dining requirements are used to generate a dish recommendation list through artificial intelligence.

[0052] Continue to refer Figure 3 In an exemplary embodiment, after the dish recommendation control 21 is expanded, the information input function can be directly displayed, such as displaying a dialog box (such as Figure 3 As shown), and prompt the user to enter dining needs in the dialog box. Figure 3 In the illustrated embodiment, the user may input dining needs through the information input control 301. The information input control 301 allows for a variety of information input methods, including but not limited to text input and voice input.

[0053] In some embodiments of the present disclosure, the user can also enter the quick entry function of dining needs by long pressing, sliding, etc. on the dish recommendation control 21 displayed on page 20 without expanding the dish recommendation control 21. The quick entry function is, for example, directly turning on the microphone on the terminal device to collect the voice information input by the user. For example, after the user long presses the dish recommendation control 21 displayed on page 20, the microphone interface is displayed, and the user is guided to input the dining needs by voice through voice prompt information or text prompt information ("I'm listening", "What are your dining needs", etc.), and then automatically forms a dish recommendation list based on the dining needs input by the user through voice.

[0054] In some embodiments, in order to improve the user's ordering efficiency, options can be directly displayed in the dish recommendation control 21, so that the user can quickly input dining needs by clicking on the options.

[0055] In an exemplary embodiment, a first demand selection list can be displayed through a dish recommendation control, the first demand selection list including multiple options for a first dining demand, the first dining demand including one of dish flavor, number of people, and price; then, in response to the user's selection operation on the first demand selection list, a second demand selection list can be displayed through the dish recommendation control, the second demand selection list including multiple options for a second dining demand, and the second dining demand is different from the first dining demand.

[0056] In this method, each dining demand occupies a demand selection list, and the number of options in the demand selection list depends on the type of the dining demand.

[0057] When the options in the demand selection list are single choices, the user's selection of the demand selection list can trigger recording of the selection result, calling out the next demand selection list, or directly entering into the formation of a dish recommendation list.

[0058] When the options in the demand selection list are multiple choices, functions such as an "OK" button can be provided to obtain the options selected by the user, record the selection results, call out the next demand selection list, or directly enter the formation of a dish recommendation list when the user operates the function.

[0059] When the user directly enters the quick entry function of dining needs by long pressing, sliding, etc. on the dish recommendation control 21 displayed on page 20, if it is detected that the dining needs entered by the user lack the necessary conditions for generating a dish recommendation list, the first demand selection list can be automatically displayed based on the missing necessary conditions for the user to supplement the dining needs. If there are many types of the necessary conditions that are missing, such as the lack of number of people information and dietary taboo information, and there can be multiple options corresponding to each necessary condition, then the options corresponding to each necessary condition can be displayed in multiple demand selection lists. That is, after the user supplements the necessary conditions for generating a dish recommendation list by selecting the first demand selection list, if the necessary conditions for generating a dish recommendation list are still not met, the second demand selection list and the third demand selection list will continue to be displayed until the necessary conditions for generating a dish recommendation list are completed.

[0060] Figure 4A and Figure 4B 2 is a schematic diagram of inputting dining requirements in an exemplary embodiment of the present disclosure.

[0061] refer to Figure 4A In some embodiments, the first dining requirement is, for example, the number of people.

[0062] A dish recommendation control 21 may be displayed at the lower portion of the page 20, and an option 401 corresponding to the first dining requirement, namely, a number of people option, may be displayed in the dish recommendation control 21. The number of people option may include commonly used number of people options such as 1-9, and an "other" option.

[0063] When the user clicks on a commonly used number of people option such as 1-9, the selection result is recorded and the next required selection list is called out. When the user clicks on the "Other" option, a number input function (such as adding or subtracting the number of people or directly entering a number) and a confirmation function (or a similar function such as "Submit") can be provided for the user to enter the number of people through the number input function and submit the number input result through the confirmation function. In this case, when the user submits the number input result through the confirmation function, the selection result can be recorded and the next required selection list can be called out.

[0064] refer to Figure 4B In some embodiments, the second dining requirement is, for example, a per capita budget.

[0065] The options 402 corresponding to the second dining requirement, i.e., the options corresponding to different per capita budget ranges, can be displayed by updating the display content in the dish recommendation control 21. When the user clicks on a common number of people option such as 1-9, the selection result is recorded and the next requirement selection list is called out, or the user directly enters the creation of a dish recommendation list.

[0066] In addition to the two exemplary demand selection lists corresponding to dining needs mentioned above, more demand selection lists corresponding to dining needs can be set, such as a taste preference selection list, which contains options corresponding to multiple taste preferences ("like to eat meat", "like to eat sweet", "don't eat spicy food", etc.); or, the user wants to order a few meat dishes, a few vegetarian dishes, a few staple foods, etc., which can all be achieved through the demand selection list.

[0067] Except for the first requirement selection list, subsequent requirement selection lists can be called out by operating the previous requirement selection list, and are not listed here one by one.

[0068] The demand selection list can quickly collect user needs in multiple dimensions, help users select needs that they may have overlooked, shorten the time users spend inputting dining needs, improve information collection efficiency, and greatly improve users' ordering efficiency.

[0069] In some cases, the collection of user dining needs can be completed by displaying multiple demand selection lists; in other cases, in order to prevent users from having selection needs that are not covered by the demand selection list, a demand input function is provided after displaying the options, or at the same time. Figure 3 The information input control 301 shown allows the user to input dining needs through text or voice, and dining needs include but are not limited to preferred flavors, dietary restrictions, user age information (such as the presence of elderly people and children), user dining scenarios (such as business banquets or family gatherings), and other types of information.

[0070] The demand input function may appear after the demand selection list is displayed to reduce the user's repeated input of information. In some embodiments, an entry for the demand input function (e.g., an "input more" button) and a skip demand input function (e.g., a "confirm dining demand" button) may be provided in the last demand selection list. If the user operates the entry for the demand input function (e.g., clicks the "input more" button), the demand input function may be displayed, for example Figure 3 The information input control 301 shown is used to collect more dining needs; if the user skips the demand input function, the user directly enters the formation of a dish recommendation list.

[0071] The embodiment of the present disclosure provides users with two dining demand provision methods: direct selection and information input, which can improve the efficiency of ordering and collect more comprehensive dining demands.

[0072] In step S3, a dish recommendation list formed according to the dining demand is displayed, the dish recommendation list includes at least one dish corresponding to the target store, and the dish recommendation list displays the dishes according to the dish category.

[0073] The embodiment of the present disclosure can use an AI big model to form a dish recommendation list based on the user's dining needs.

[0074] Figure 5 It is a sub-flowchart for forming a dish recommendation list in an exemplary embodiment of the present disclosure.

[0075] refer to Figure 5 In an exemplary embodiment, step S3 may include:

[0076] Step S31, obtaining the user's historical dining consumption records, and determining the user's ordering preferences based on the historical dining consumption records;

[0077] Step S32: Obtain recommended dishes of the target store, including store recommended dishes and user recommended dishes;

[0078] Step S33, determining one or more target dishes based on dining needs, the user's ordering preferences, and the target store's recommended dishes;

[0079] Step S34: forming a dish recommendation list based on one or more target dishes.

[0080] In the background, the AI ​​model can access the user's historical dining consumption records through the user's current account, obtain the dishes consumed by the user in a preset time period (for example, the past year) and the evaluation of the dishes (the evaluation can be empty), and then analyze the user's ordering preferences based on multiple dimensions such as the flavor type (such as sweet, spicy), cooking method type (such as stir-fry, steaming, grilling), and ingredient type (such as meat, seafood, vegetables). Ordering preferences can include flavor preferences such as spicy food, meat, grilling, ingredient preferences, or cooking method preferences, as well as characteristic labels such as "staple food control" and "meat lover".

[0081] The user's ordering preferences can be updated regularly in the background and directly read when used, thereby improving the efficiency of forming a recommended dish list.

[0082] In addition to the user's ordering preferences, the disclosed embodiment also refers to the recommended dishes of the target store to form a recommended dish list. The recommended dishes of the target store include at least the store recommended dishes set by the store, and the user recommended dishes formed by the platform based on user feedback. When analyzing the recommended dishes, feature extraction can be performed according to factors such as the degree of recommendation, dish taste, type of ingredients, cooking method, price, etc., so as to give the number and name of different types of dishes through comprehensive matching through the AI ​​big model based on the recommended dishes and the user's ordering preferences extracted from the background and the dining needs input by the user in real time. In this process, dining needs have the highest priority, and recommended dishes and ordering preferences are reference items.

[0083] Determining the types of dishes in the recommended dish list (for example, meat dishes, vegetarian dishes, and staple foods in Chinese cuisine, and appetizers, main courses, desserts, etc. in Western cuisine), the quantity of each dish (determined based on the number of people and the portion size), and the specific dishes included in each dish (for example, meat dishes include braised pork) can be achieved by the AI ​​big model trained by the platform itself, or with the help of a third-party big model. The embodiments of the present disclosure do not limit the source of the big model.

[0084] Since it takes a certain amount of time to form a list of recommended dishes, in order to optimize the user's waiting experience during the process of forming the list of recommended dishes, in the embodiment of the present disclosure, a first text corresponding to the dining needs can be displayed, and / or a second text corresponding to the artificial intelligence thinking process of forming the dish recommendation results based on the dining needs can be displayed.

[0085] Figure 6A and Figure 6B is a schematic diagram of a waiting interface in an exemplary embodiment of the present disclosure.

[0086] refer to Figure 6A In the process of forming the dish recommendation list, in order to optimize the user's waiting experience, the first text 601 corresponding to the dining demand can be displayed in the dish recommendation control 21 to help the user review and confirm the dining demand. In this process, the display range of the dish recommendation control 21 can be expanded, such as Figure 6A As shown, it is clear that the user is currently waiting and the user is prompted to avoid the user continuing to operate and affecting the formation of the dish recommendation list.

[0087] refer to Figure 6B In addition, the second text 602 corresponding to the artificial intelligence thinking process of forming a dish recommendation result based on dining needs can be displayed in the dish recommendation control 21. The second text can include but is not limited to dining needs, characteristics of the target store, and consideration factors for forming a dish recommendation list.

[0088] according to Figure 5 The illustrated embodiment determines the dishes corresponding to the dish recommendation list, and after forming the dish recommendation list, displays the dish recommendation list.

[0089] Figure 7 2 is a schematic diagram of a dish recommendation list in an exemplary embodiment of the present disclosure.

[0090] refer to Figure 7 The dish recommendation list 71 may include partitions 701 corresponding to multiple dish categories (in Figure 7 The middle partition includes meat dishes, vegetarian dishes, and staple foods. Each partition 701 corresponds to at least one dish entry, and each dish entry includes information such as the dish's picture, name, characteristics, sales volume, and price.

[0091] In addition, the dish recommendation list 71 also displays the total price of the current dish combination, such as Figure 7 The price display area 702 in the.

[0092] In an exemplary embodiment, when forming a dish recommendation list, the total price of all dishes corresponding to the dish recommendation list can be obtained, and then the corresponding discount information of the user can be obtained; the settlement price corresponding to the dish recommendation list is determined based on the discount information and the total price; and the total price, discount information and settlement price are displayed in the dish recommendation list.

[0093] like Figure 7 As shown, the original price (￥223) is automatically displayed, along with the discount (￥23) and the final price after the discount (￥203, which takes into account the table fee). This eliminates the need for users to collect discount information and adjust their dishes. Instead, they can directly see the final price corresponding to the current dish combination, greatly improving their ordering efficiency.

[0094] In the embodiment of the present disclosure, the dish recommendation list 71 and the dish recommendation control 21 are displayed on the screen simultaneously, so that the user can continue to operate the dish recommendation control 21 to adjust the dishes in the dish recommendation list 71.

[0095] In some embodiments, in order to further improve efficiency, multiple dish recommendation lists 71 can be formed at the same time, and only one is displayed at a time, allowing the user to change the dish recommendation list 71 by sliding or clicking, etc. Figure 7 As shown. Different dish recommendation lists 71 correspond to different dishes, so that the user can easily select one of the multiple dish recommendation lists 71 (i.e., the one currently displayed on the screen) and adjust the dishes in the dish recommendation list 71 currently displayed on the screen through the dish recommendation control. The triggering method for adjusting the dish recommendation list 71 is, for example, clicking the dish recommendation control 21 to expand the dish recommendation control 21.

[0096] In step S4, in response to the user's selection operation or input operation on the dish recommendation control, the changed dining requirements are sent to the artificial intelligence, the dish recommendation list is updated through the artificial intelligence, and the updated dish recommendation list is displayed.

[0097] In an exemplary embodiment, the user can replace part or all of the dishes in the dish recommendation list through a selection operation or an input operation, or request to regenerate a completely different dish recommendation list.

[0098] Figures 8A to 8D 3 is a schematic diagram of adjusting a menu recommendation list by inputting dining requirements in an exemplary embodiment of the present disclosure.

[0099] refer to Figure 8A, multiple dish adjustment options 801 and information input control 301 can be displayed in the dish recommendation control 21, and the multiple dish adjustment options 801 include at least adding a meat dish, adding a vegetarian dish, adding a staple food (such as Figure 8A In some embodiments, a “re-recommend” menu adjustment option may also be displayed to regenerate the menu recommendation list.

[0100] Next, based on the user's selection of at least one dish adjustment option 801 and / or the user's updated dining requirements input through the information input control 301 , the dishes in the dish recommendation list are adjusted.

[0101] For example, the user can quickly input dining needs by clicking on the dish adjustment option 801 of "add a meat dish".

[0102] refer to Figure 8B ,Users can input information to update dining needs by voice input.

[0103] refer to Figure 8C , users can enter information to update their dining needs by entering text.

[0104] refer to Figure 8D Regardless of how the user inputs their dining needs, the AI ​​model can re-form a list of recommended dishes based on the updated dining needs, and display the text corresponding to the dining needs and the text corresponding to the thinking process, such as Figure 8D shown.

[0105] During the process of inputting dining requirements, the display areas of the dish recommendation control 21 and the dish recommendation list 71 can be automatically adaptively adjusted to facilitate user viewing and operation.

[0106] In addition to updating dining requirements to adjust the dish recommendation list as described above, the user can also directly replace individual dishes in the dish recommendation list. In some embodiments, the user can also directly add or subtract dishes from the dish recommendation list.

[0107] Figure 9 2 is a schematic diagram of a selection control for recommending dishes in an exemplary embodiment of the present disclosure.

[0108] refer to Figure 9In an exemplary embodiment, at least one recommended dish selection control 901 may be displayed in the dish recommendation control 21. The recommended dish selection control 901 displays the image and price of the recommended dish. Then, in response to the user's selection operation on the recommended dish selection control 901, the selected recommended dish is added to the dish recommendation list 71. In addition, while displaying the recommended dish selection control 901, the information input control 301 may also be displayed. For the usage of the information input control 301, please refer to Figures 8B to 8D .

[0109] Among them, whether it is Figure 8A The menu adjustment options 801 and information input control 301 shown are still Figure 9 The selection control 901 of the recommended dishes can be displayed after the user clicks the dish recommendation control 21. Figure 8A and Figure 9 The two recommended adjustment methods of dishes shown can be selected to display one of them, or they can be displayed in sequence, for example, display Figure 9 The selection control 901 shown, then displays Figure 8A The dish adjustment option 801 shown, or, at the same time, the selection control 901 and the dish adjustment option 801 are displayed. Regardless of the method used for quick display, the information input control 301 can be displayed.

[0110] In addition, in the dish recommendation list 71, a dish change button 902 (such as Figure 9 button shown) to allow users to change dishes individually.

[0111] When the user clicks the dish change button 902, the AI ​​big model can automatically determine one or more recommended dishes based on the dish corresponding to the dish change button 902, and display the one or more recommended dish selection controls 901 in the dish recommendation control 21, so that the user can quickly replace the dish.

[0112] Figure 10 2 is a schematic diagram of an adjusted dish recommendation list in an exemplary embodiment of the present disclosure.

[0113] refer to Figure 10 , when a dish is added (such as Figure 10 After adding the dish in the recommended dish list 71, the "new dish" label is marked in the entry corresponding to the dish added in the recommended dish list 71. At the same time, the virtual shopping cart 101 is updated according to the dishes in the recommended dish list 71, and the number of dishes in the virtual shopping cart is displayed (such as Figure 10 ”4” in the .

[0114] The user can continue to operate the dish recommendation control 21 to continue changing dishes, adding dishes or deleting dishes. The updated dish recommendation list not only updates the dish items, but also synchronously updates the settlement price corresponding to the current dish recommendation list.

[0115] The user can view the ordered dishes by sliding the dish recommendation list 71, or click the dish recommendation control 21 or the dish change button 902 to expand the dish recommendation control 21 to update the dining requirements or directly adjust the dish items in the dish recommendation list 71.

[0116] In an exemplary embodiment, in addition to the user's active triggering of adjustments to the dish recommendation list 71, the current dish recommendation list 71 can also be automatically matched to find the target store's online group purchase packages, coupons, and payment discounts, etc., to automatically determine the best discount method, eliminating the trouble of users manually buying coupons and packages.

[0117] For example, in the process of forming the dish recommendation list 71, if it is determined that the dish combination in the dish recommendation list 71 to be generated has a similarity with the dish combination in a group purchase package of the target store that exceeds a preset value (for example, 70%), or, after the user adjusts the dish recommendation list 71, it is found that the dish recommendation list adjusted by the user has a similarity with the dish combination in a group purchase package of the target store that exceeds a preset value (for example, 70%), then the dish recommendation list is formed based on the dishes corresponding to the group purchase package, and the group purchase package is used as one of the dish recommendation lists formed, or the only dish recommendation list, and the current dish combination corresponds to the group purchase package, as well as the discount range of the group purchase package.

[0118] By automatically matching group purchase packages in the process of forming a recommended list of dishes, we can greatly save users' ordering time while providing them with the greatest discount plans, further optimizing the user experience.

[0119] In order to facilitate the user's operation of the dish recommendation list 71 and the dish recommendation control 21, in the embodiment of the present disclosure, it is set that the user can adjust the display scheme of the dish recommendation list 71 and the dish recommendation control 21.

[0120] Figure 11 It is a schematic diagram of adjusting the display of a dish recommendation list and a dish recommendation control in an exemplary embodiment of the present disclosure.

[0121] refer to Figure 11 In an exemplary embodiment, a dish recommendation list 71 is displayed in the first area 11 of the page 20, a dish recommendation control 21 is displayed in the second area 12 of the page 20, and a partition adjustment control 13 is provided between the first area 11 and the second area 12.

[0122] like Figure 11 As shown from left to right, the area of ​​the first area 11 and the area of ​​the second area 12 can be adjusted on the page in response to the user's sliding operation on the partition adjustment control 13, thereby allowing the user to expand the display area of ​​the dish recommendation list 71, or expand the display area of ​​the dish recommendation control 21 to facilitate user viewing or operation.

[0123] Regardless of whether the dish recommendation list 71 is adjusted, after deciding to order dishes based on the current dish recommendation list 71 , the user can click on the dish recommendation control 21 to add the dishes in the dish recommendation control 21 to the virtual shopping cart.

[0124] In addition to calling out the dish recommendation control 21 for the first time after accessing the page 20, after forming the dish recommendation list 71 or adjusting the dish recommendation list 71, such as Figure 10 As shown, after adding the dishes in the dish recommendation list 71 to the virtual shopping cart 101, the dish recommendation control 21 can also be called out by clicking on the virtual shopping cart 101, that is, the dish recommendation control 21 is integrated into the display interface of the virtual shopping cart 101 to allow the user to adjust the dishes in the virtual shopping cart before forming a user order.

[0125] Figures 12A to 12C 2 is a schematic diagram of accessing a dish recommendation control through a virtual shopping cart in an exemplary embodiment of the present disclosure.

[0126] refer to Figure 12A When the user has formed a dish recommendation list for the target store, or adjusted the dish recommendation list, the entrance to the virtual shopping cart 101 can be displayed in the dish recommendation control 21 on the page 20 of the target store.

[0127] refer to Figure 12B After the user clicks on the entry of the virtual shopping cart 101 in the dish recommendation control 21, or performs a preset operation, the dish items 121 in the virtual shopping cart can be displayed for the user to confirm. Unlike conventional virtual shopping cart displays, in the embodiment of the present disclosure, the dish information displayed in the virtual shopping cart can also be divided into sections according to dish categories, so that the user can adjust the dishes according to the dish category.

[0128] The display format of the dish items 121 in the virtual shopping cart is different from that of the dish items in the dish recommendation list. For example, a quantity adjustment option can be added to facilitate the deletion of dishes. At the same time, the displayed information can be reduced (for example, the "Change Dish" button can be reduced).

[0129] In addition, while displaying the virtual shopping cart, the dish recommendation control 21 is displayed, and the dish adjustment control 122 (such as Figure 12B Tell me more about your needs) and the order generation control 123 (such as Figure 12B 'Proceed to Checkout' button in the .

[0130] When the user clicks the dish adjustment control 122 (such as Figure 12B When you click the "Tell me more about your needs" button in the menu, you can expand the dish recommendation control 21, such as Figure 12C As shown, the menu adjustment option 801 and the information input control 301 are displayed at the same time to allow the user to adjust the menu recommendation list again, or to make notes on dietary restrictions and other information before submitting the order.

[0131] After the user re-enters the dining requirements, the recommended dish list is updated. The subsequent operations are as described above and will not be repeated here. If the information entered by the user is information such as dietary restrictions, the information is recorded and added to the user's order.

[0132] When the user clicks the order generation control 123 in the dish recommendation control 21, the settlement page is entered.

[0133] In step S5, in response to the user's preset settlement operation on the dish recommendation control, a user order is formed according to the dish recommendation list.

[0134] Continue to refer Figure 12A and Figure 12B In an exemplary embodiment, the preset settlement operation is implemented by, for example, clicking the order generation control 123 in the current dish recommendation control 21.

[0135] After the user performs the preset checkout operation, a user order corresponding to the target store can be generated for the dishes in the virtual shopping cart.

[0136] In the embodiment of the present disclosure, the method of forming a dish recommendation list and automatically forming an order can be used in a variety of scenarios. Therefore, when forming a user order, it is possible to first check whether the user provides table number information.

[0137] Figure 13 It is a sub-flow chart of forming a user order in an exemplary embodiment of the present disclosure.

[0138] refer to Figure 13 In an exemplary embodiment, step S5 may include:

[0139] Step S51, responding to the user's preset settlement operation on the dish recommendation control, determining the user's current table number information in the target store;

[0140] Step S52: When the table number information is empty, a code scanning function or a table number input function is displayed to prompt the user to provide the table number information;

[0141] Step S53: forming a user order corresponding to the target store based on the dishes and table number information in the dish recommendation list.

[0142] exist Figure 13 In the illustrated embodiment, during the process of forming a user order, it may be first determined whether the user has table number information corresponding to the target store.

[0143] When the user enters the page of the target store through the scan code ordering entrance of the store table, the table number information can be automatically obtained in step S51, and there is no need to enter step S52 at this time; when the user only browses the page corresponding to the target store through the application, the table number information cannot be obtained in step S51. Therefore, the user can be reminded to enter the table number information through a pop-up window or other means (by scanning the scan code ordering entrance of the store table to obtain the table number information, or directly entering the table number), so that a user order corresponding to the table number is formed for the target store in step S53, and the user order is sent to the management backend of the target store for the target store to deliver the food.

[0144] After obtaining the table number information, you can enter the order confirmation page.

[0145] Figure 14 2 is a schematic diagram of an order confirmation page in an exemplary embodiment of the present disclosure.

[0146] refer to Figure 14 On the order confirmation page, the dish items, price information and table number information can be displayed (the table change function allows the user to adjust the table number), and at the same time, the dish recommendation control 21 can be displayed. The dish adjustment control 122 can also be provided in the dish recommendation control 21. The text content corresponding to the dish adjustment control 122 can be changed according to different ordering links, for example, Figure 14 In the example, the text content is to prompt the user to enter dietary information. Regardless of the text content, the user can adjust the dining needs by clicking the dish adjustment control 122. If there is no need to continue adjusting the dining needs, the user can click the order generation control 123 to enter the payment interface (not shown) to make payment.

[0147] After the user pays successfully, the user's order will be sent to the backend of the target store.

[0148] In summary, the disclosed embodiments incorporate AI capabilities into in-store ordering scenarios, creating an AI waiter role (smart ordering assistant) to assist users in ordering. Based on the user's dining needs, consumption preferences, and the target store's recommended dishes, the system automatically provides the optimal dish combination to form a recommended dish list, while also supporting adjustments to the overall menu and individual dishes.

[0149] Multiple ordering steps continue to appear before the user places an order, creating the perception of an offline waiter accompanying the user to order. It also supports voice and text input, allowing users to communicate with the AI ​​assistant in real time and adjust the overall menu and individual dishes.

[0150] It should be noted that although several modules or units of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0151] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided, such as various terminal devices such as a mobile phone and a tablet computer.

[0152] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods, or program products. Therefore, various aspects of the present invention may be implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits," "modules," or "systems."

[0153] Refer to the following Figure 15 An electronic device 1500 according to this embodiment of the present invention will be described. Figure 15 The electronic device 1500 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0154] like Figure 15 As shown, electronic device 1500 is implemented as a general-purpose computing device. Components of electronic device 1500 may include, but are not limited to, the aforementioned at least one processing unit 1510, the aforementioned at least one storage unit 1520, and a bus 1530 connecting various system components (including storage unit 1520 and processing unit 1510).

[0155] The storage unit stores program code, which can be executed by the processing unit 1510, so that the processing unit 1510 performs the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section above. For example, the processing unit 1510 can perform the method described in the embodiments of the present disclosure.

[0156] The storage unit 1520 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 15201 and / or a cache 15202 , and may further include a read-only memory unit (ROM) 15203 .

[0157] The storage unit 1520 may also include a program / utility 15204 having a set (at least one) of program modules 15205, such program modules 15205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0158] Bus 1530 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0159] Electronic device 1500 can also communicate with one or more external devices 1600 (e.g., a keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 1500, and / or any device that enables electronic device 1500 to communicate with one or more other computing devices (e.g., a router, modem, etc.). Such communication can occur via input / output (I / O) interface 1550. Furthermore, electronic device 1500 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via network adapter 1560. As shown, network adapter 1560 communicates with other modules of electronic device 1500 via bus 1530. It should be understood that, although not shown, other hardware and / or software modules can be used in conjunction with electronic device 1500, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0160] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0161] In exemplary embodiments of the present disclosure, a computer-readable storage medium is also provided, on which is stored a program product capable of implementing the aforementioned methods of this specification. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product comprising program code. When the program product is executed on a terminal device, the program code is configured to cause the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section of this specification.

[0162] The program product for implementing the above-described method according to an embodiment of the present invention may be a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0163] The program product may be implemented in any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0164] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0165] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0166] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0167] Furthermore, the above-described figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above-described figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0168] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the claims.

Claims

1. A dish recommendation method, characterized in that: include: Display a dish recommendation control on the page corresponding to the target store, where the target store is displayed in the merchant mini program or in the application of the life service e-commerce platform; The dish recommendation control receives dining requirements input by the user, wherein the dining requirements include at least dish taste, number of people, and price range, and the dining requirements are used to generate a dish recommendation list through artificial intelligence; Displaying a dish recommendation list formed according to the dining demand, the dish recommendation list including at least one dish corresponding to the target store, and the dish recommendation list displaying the dishes by dish category; In response to a user's selection operation or input operation on the dish recommendation control, the changed dining requirements are sent to the artificial intelligence, the dish recommendation list is updated by the artificial intelligence, and the updated dish recommendation list is displayed; In response to the user's preset settlement operation on the dish recommendation control, a user order is formed according to the dish recommendation list.

2. The dish recommendation method according to claim 1, wherein: Receiving user input of dining requirements through the dish recommendation control includes: The dish recommendation control receives a dining requirement input by a user, and when detecting that the dining requirement input by the user lacks a necessary condition for generating a dish recommendation list, displays a first requirement selection list through the dish recommendation control, wherein the first requirement selection list includes multiple options of the first dining requirement, and the first dining requirement includes one of a dish taste, a number of people, and a price range; In response to the user's selection operation on the first demand selection list, and when the necessary conditions for generating a dish recommendation list are still not met, a second demand selection list is displayed through the dish recommendation control, and the second demand selection list includes multiple options for a second dining demand, and the second dining demand is different from the first dining demand.

3. The dish recommendation method according to claim 1, wherein: The display of the recommended list of dishes formed according to the dining needs includes: Display the first copy corresponding to the dining demand and the second copy corresponding to the artificial intelligence thinking process of forming the dish recommendation result based on the dining demand.

4. The dish recommendation method according to claim 1, wherein: The method of generating a recommended dish list through artificial intelligence includes: Obtaining the user's historical dining consumption records, and determining the user's ordering preferences based on the historical dining consumption records; Obtaining recommended dishes of the target store, wherein the recommended dishes include store recommended dishes and user recommended dishes; Determining one or more target dishes according to the dining demand, the user's ordering preferences, and the recommended dishes of the target store; The dish recommendation list is formed according to the one or more target dishes.

5. The dish recommendation method according to claim 1, wherein: The display of the recommended list of dishes formed according to the dining needs includes: Obtain the total price of all dishes corresponding to the recommended dish list; Obtaining preferential information corresponding to the user; Determining the settlement price corresponding to the recommended dish list based on the discount information and the total price; The total price, the discount information and the settlement price are displayed in the dish recommendation list.

6. The dish recommendation method according to claim 1, wherein: In response to a user's selection operation or input operation on the dish recommendation control, sending the modified dining requirement to the artificial intelligence, and updating the dish recommendation list through the artificial intelligence includes: Displaying multiple dish adjustment options and an information input control in the dish recommendation control, wherein the multiple dish adjustment options include at least adding a meat dish, adding a vegetarian dish, adding a staple food, and re-recommending; The dishes in the dish recommendation list are adjusted according to the user's selection operation of at least one of the dish adjustment options and / or the updated dining requirements input by the user through the information input control.

7. The dish recommendation method according to claim 1 or 6, characterized in that: In response to a user's selection operation or input operation on the dish recommendation control, sending the modified dining requirement to the artificial intelligence, and updating the dish recommendation list through the artificial intelligence includes: A dish replacement button is provided for each dish in the displayed dish recommendation list, and the dish replacement button is used to replace the corresponding dish; In response to the user's operation on the dish change button, at least one recommended dish selection control is displayed in the dish recommendation control according to the dish corresponding to the dish change button, and the recommended dish selection control displays a picture and price of the recommended dish; In response to the user's selection operation on the selection control of the recommended dish, the selected recommended dish is added to the dish recommendation list.

8. The dish recommendation method according to claim 1, wherein: Also includes: Displaying the entrance to the virtual shopping cart, the dish adjustment control, and the order generation control in the dish recommendation control; In response to a user's operation on an entry to the virtual shopping cart, displaying dish items corresponding to dishes in the virtual shopping cart, where the dishes in the virtual shopping cart are determined according to the dish recommendation list; In response to a user operation on the dish adjustment control, expanding a dish recommendation control, and displaying dish adjustment options and an information input control in the dish recommendation control; In response to the user's operation on the order generation control, a checkout interface is formed according to the dishes in the virtual shopping cart; The settlement interface is displayed for the user to pay and form the user order.

9. The dish recommendation method according to claim 1, wherein: In response to a preset settlement operation of the user on the dish recommendation control, forming a user order according to the dishes in the dish recommendation list includes: In response to a preset settlement operation of the dish recommendation control by the user, determining the table number information of the user at the target store; When the table number information is empty, display a code scanning function or a table number input function to prompt the user to provide the table number information; A user order corresponding to the target store is formed according to the dishes in the dish recommendation list and the table number information.

10. An electronic device, characterized in that: include: Memory; as well as A processor coupled to the memory, the processor being configured to execute the method according to any one of claims 1 to 9 based on instructions stored in the memory.

Images