Pet product order push method and related device

Abstract

This application provides a method and related apparatus for pushing pet product orders. The method includes: obtaining product information of the pet's products to be purchased, obtaining a nose print image of the pet, obtaining profile information corresponding to the pet based on the nose print image, determining an order template based on the products to be purchased, determining order data corresponding to the order template from the product information of the products to be purchased based on the order template and the profile information, filling the order data into the order template to obtain the target order for the products to be purchased, and sending the target order to the target user corresponding to the pet. This method can fill in the order for the pet's products to be purchased based on the product information and nose print image of the pet, and push it to the user, thereby eliminating the need for the user to fill in order data item by item, improving the intelligence of pet product order push and enhancing the user experience.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a method and related apparatus for pushing pet product orders. Background Technology

[0002] With the rapid development of electronic device technology, intelligent control technology, represented by artificial intelligence, is permeating all aspects of human life. Currently, when consumers purchase pet supplies online, they need to select items and then choose the necessary information to generate an order. Therefore, when purchasing pet supplies online, users need to select and / or fill in order data, which is a complex and inconvenient process. Summary of the Invention

[0003] This application provides a method and related apparatus for pushing pet product orders. The method fills in the order information of the pet's products to be purchased and the pet's nose print image, and pushes it to the user. The aim is to eliminate the need for the user to fill in the order data item by item, improve the intelligence of pet product order push and enhance the user experience.

[0004] A first aspect of this application provides a method for pushing pet product orders. The method includes: obtaining product information of a product to be purchased for a pet, and obtaining a nose print image of the pet; obtaining profile information corresponding to the pet based on the nose print image; determining an order template based on the product to be purchased; determining order data corresponding to the order template from the product information of the product to be purchased based on the order template and the profile information; filling the order data into the order template to obtain a target order for the product to be purchased; and sending the target order to a target user corresponding to the pet.

[0005] As can be seen, since the server can fill in the order information of the pet's pending purchase items based on the pet's nose print image and push it to the user, the user does not need to fill in the order data item by item. This improves the intelligence of pet product order push and enhances the user experience.

[0006] In one possible example, determining the order data corresponding to the order template from the product information of the product to be purchased, based on the order template and the file information, includes: determining at least one field to be filled in the order template; obtaining product feature information for each of the at least one field to be filled; determining reference product feature values ​​corresponding to the product feature information of each of the at least one field to be filled from the product information of the product to be purchased; and performing the following operations on the reference product feature values ​​corresponding to the product feature information of each of the at least one field to be filled to obtain a target feature value for each of the at least one field to be filled: obtaining the target number of m reference product feature values ​​corresponding to the target product feature information of the currently processed field to be filled; if the target number is greater than or equal to 2, then determining the product feature value with the highest total matching score of the pet among the m reference product feature values ​​based on the target product feature information of the currently processed field to be filled and the file information; if the target number is equal to 1, then determining the m product feature values ​​as the target feature value.

[0007] In this example, by extracting the product feature information of each of the at least one field to be filled in the order template, a reference product feature value corresponding to the product feature information of each of the at least one field to be filled is determined from the product information of the product to be purchased. Then, a target feature value for each field to be filled is determined from the reference product feature value. When there is more than one reference product feature value for a field to be filled, the product feature value with the highest total matching score with the pet is determined based on the pet profile and the target product feature information of the field to be filled, and thus the value to be filled in is determined. Therefore, filling in the feature value of the field to be filled based on the product information, the target product feature information of the field to be filled, and the pet profile of the pet can greatly improve the matching degree between the feature value of the field to be filled and the pet when generating an order.

[0008] In one possible example, determining the target feature value as the product feature value with the highest matching degree among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the profile information includes performing the following operations for each of the m product reference feature values ​​based on the profile information and the product feature information: determining the product feature type of the currently processed item to be filled based on the target product feature information; if the product feature type is clothing color, determining a first matching score between the pet and the currently processed product reference feature value based on the pet's personality in the profile information; determining a second matching score between the pet and the currently processed product reference feature value based on the pet's fur color in the profile information; and determining a total matching score between the pet and the currently processed product reference feature value based on the first matching score and the second matching score.

[0009] In this example, when the product feature category to be filled in is clothing color, the server can determine the total matching score between the pet and the product reference feature value based on the pet's fur color and personality in the pet profile information. Since the product feature value with the highest total matching score is the value entered in the product field, and the total matching score is determined based on the pet's fur color and personality in the pet profile information, this embodiment of the application helps to ensure that the pet matches the value entered in the clothing color field of the order.

[0010] In one possible example, determining the total matching score between the pet and the currently processed product reference feature value based on the first matching score and the second matching score includes: obtaining color preference information of the target user for the product to be purchased; determining a third matching score between the target user and the currently processed product reference feature value based on the color preference information; and determining the total matching score based on the first matching score, the second matching score, and the third matching score.

[0011] In this example, when the product feature category to be filled in is clothing color, the server can determine the total matching score between the pet and the product reference feature value based on the pet's fur color, pet personality, and the target user's color preference information for the product to be purchased, according to the pet's profile information. Since the product feature value with the highest total matching score is the value entered in the product field, and the total matching score is determined based on the pet's fur color and pet personality in the pet's profile information, this embodiment of the application helps to ensure that both the pet and the user's preferences match the value entered in the clothing color field of the order.

[0012] In one possible example, after determining the product feature type of the currently processed item to be filled based on the target product feature information, the method further includes: if the product feature type is food flavor, then determining a fourth matching score between the target user and the currently processed product reference feature value based on the pet's taste preferences in the profile information; determining a fifth matching score between the pet and the currently processed product reference feature value based on the disease information in the profile information; and determining a total matching score between the pet and the currently processed product reference feature value based on the fourth matching score and the fifth matching score.

[0013] In this example, when the product feature category to be filled in is food flavor, the server can determine the total matching score between the pet and the product reference feature value based on the pet's taste preferences and disease information in the pet's profile information. Since the product feature value with the highest total matching score is the value entered in the product feature category, and the total matching score is determined based on the pet's taste preferences and disease information in the pet's profile information, this embodiment of the application helps to ensure that the pet matches the value entered in the food flavor field of the order.

[0014] A second aspect of this application provides a pet product order push device, the device comprising: a first acquisition unit, configured to acquire product information of a product to be purchased by a pet, and to acquire a nose print image of the pet; a second acquisition unit, configured to acquire profile information corresponding to the pet based on the nose print image; a first determination unit, configured to determine an order template based on the product to be purchased; a second determination unit, configured to determine order data corresponding to the order template from the product information of the product to be purchased based on the order template and the profile information; an order generation unit, configured to fill the order data into the order template to obtain a target order for the product to be purchased; and a sending unit, configured to send the target order to a target user corresponding to the pet.

[0015] A third aspect of this application provides a server including a processor, an input device, an output device, and a memory, wherein the processor, input device, output device, and memory are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to execute the step instructions as described in the first aspect of this application.

[0016] A fourth aspect of this application provides a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of this application.

[0017] A fifth aspect of this application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of this application. The computer program product may be a software installation package.

[0018] Implementing the embodiments of this application has at least the following beneficial effects:

[0019] First, the system obtains the product information of the pet's items to be purchased, as well as the pet's nose print image. Then, it retrieves the corresponding profile information based on the nose print image. Next, it determines the order template based on the items to be purchased. Then, based on the order template and the profile information, it identifies the order data corresponding to the order template from the product information of the items to be purchased. Finally, it fills the order data into the order template to obtain the target order for the items to be purchased. Finally, it sends the target order to the target user corresponding to the pet. Therefore, it can fill in the order for the pet's items to be purchased based on the pet's product information and nose print image, and push it to the user. This eliminates the need for the user to fill in order data item by item, improving the intelligence of pet product order push and enhancing the user experience. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of an order push system provided in an embodiment of this application;

[0022] Figure 2 A flowchart illustrating a pet product order push method provided in an embodiment of this application;

[0023] Figure 3 A flowchart illustrating another pet product order push method provided in this application embodiment;

[0024] Figure 4A This application provides an embodiment of a scenario where a user purchases pet items online and receives a push notification for a pet product order.

[0025] Figure 4B This application provides an illustration of a scenario where a user receives a push notification for pet products while shopping at a supermarket.

[0026] Figure 5 This application provides a schematic diagram of the structure of a server according to an embodiment of the present application.

[0027] Figure 6 This is a schematic diagram of a pet product order push device provided in an embodiment of this application. Detailed Implementation

[0028] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0030] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0031] The electronic devices involved in the embodiments of this application can be electronic devices with fingerprint recognition capabilities. These electronic devices can include various handheld devices, computing devices, and access control devices with fingerprint recognition functions, as well as various forms of user equipment (UE), mobile stations (MS), etc.

[0032] Currently, when consumers purchase pet items online, they need to select the items and then choose the items to generate the order. Therefore, when purchasing pet items online, users need to select and / or fill in order data, which is complicated and inconvenient.

[0033] To address the aforementioned issues, this application provides an information push method based on pet nose prints.

[0034] To better understand the pet product order push method provided in this application embodiment, a brief introduction to the order push system applying the pet product order push method is given below. For example... Figure 1As shown, the order push system 100 may include an electronic device 110 for information collection and a server 120 for information processing and order push. The electronic device 110 and the server 120 are connected by communication. The electronic device 110 can acquire the pet's intended purchase items and the pet's nose print image. The electronic device 110 can acquire the pet's product information through user input or by receiving data. The electronic device 110 can acquire the pet's nose print image by recognizing the pet's face. Then, the electronic device 110 sends the acquired product information and nose print image to the server 120. The server 120 obtains the pet's corresponding profile information based on the nose print image and determines an order template based on the intended purchase items. The server 120 determines the order data corresponding to the order template from the product information of the intended purchase items based on the order template and profile information. The server 120 fills the order data into the order template to obtain the target order for the intended purchase items. The server 120 sends the target order to the target user corresponding to the pet. Server 120 can fill in the pet's order for the items to be purchased based on the pet's product information and the pet's nose print image, and push it to the user. This eliminates the need for the user to fill in the order data item by item, improving the intelligence of the pet product order push and enhancing the user experience.

[0035] Please see Figure 2 , Figure 2 This application provides a flowchart illustrating a method for pushing pet product orders. Figure 2 As shown, this method can be applied to a server, and the method includes:

[0036] 201. Obtain the product information of the pet's items to be purchased, and obtain the pet's nose print image.

[0037] The product information may include, but is not limited to, all models, colors, names, and flavors of the product currently in stock and available for purchase.

[0038] For example, if the product to be purchased includes yellow, white, black, and blue, then the product information includes all four colors. If the product to be purchased includes blueberry, apple, tomato, strawberry, and chocolate flavors, then the product information includes all five flavors. If the name of the product to be purchased is "Robot Xiaoming," then the product information includes the product name "Robot Xiaoming," and so on, without specific limitations.

[0039] In a specific implementation, the server can obtain product information of the pet to be purchased and the pet's nose print image through an electronic device. For example, the electronic device can display an item search interface for the items to be purchased, which includes a first control; upon detecting a first operation on the first control, a first sub-control and a second sub-control are displayed; upon detecting a second operation on the first sub-control, a local camera image capture interface is displayed, allowing the user to capture the nose print image of the target pet; upon detecting a third operation on the second sub-control, the initial page of the electronic device's local image library is displayed, allowing the user to select the target pet's nose print image from the local image library. After the user selects an item to be purchased from the products pushed based on the nose print image, the electronic device can display an order interface for the item to be purchased, which includes an order confirmation button. Upon detecting a fourth operation on the order confirmation button, the electronic device obtains the unique identifier of the item to be purchased and the nose print image, and sends the unique identifier and the nose print image to the server. The server completes the acquisition of the nose print image. After receiving the unique identifier, the server retrieves the product information of the item to be purchased from the item database based on the unique identifier.

[0040] The first operation, the second operation, the third operation, and the fourth operation can be any of the following: a single click, multiple clicks, or a swipe operation.

[0041] 202. Obtain the file information corresponding to the pet based on the nose print image.

[0042] The server retrieves the pet's profile information corresponding to the nose print image from memory. This profile information includes, but is not limited to, the pet's fur color, personality, and food preferences.

[0043] 203. Determine the order template based on the goods to be purchased.

[0044] The correspondence between the products to be purchased and the order templates is pre-defined, and the order template corresponding to the product to be purchased can be determined from the template database.

[0045] 204. Based on the order template and the file information, determine the order data corresponding to the order template from the product information of the goods to be purchased.

[0046] 205. Fill the order data into the order template to obtain the target order for the goods to be purchased.

[0047] 206. Send the target order to the target user corresponding to the pet.

[0048] The target order is an editable order, and users can modify the order data on the target order.

[0049] As can be seen in this example, the server can obtain the product information of the pet's items to be purchased, as well as the pet's nose print image. Based on the nose print image, it retrieves the corresponding profile information for the pet. It determines the order template based on the items to be purchased, and based on the order template and profile information, it identifies the order data corresponding to the order template from the product information of the items to be purchased. The order data is then filled into the order template to obtain the target order for the items to be purchased, and the target order is sent to the target user corresponding to the pet. Therefore, the server can fill in the order for the pet's items to be purchased based on the pet's product information and nose print image, and push it to the user. This eliminates the need for the user to fill in order data item by item, improving the intelligence of pet product order push and enhancing the user experience.

[0050] In one possible implementation, the method for determining the order data corresponding to the order template from the product information of the goods to be purchased based on the order template and the file information may include, but is not limited to:

[0051] A1. Identify at least one field to be filled in the order template;

[0052] A2. Obtain the product feature information of each of the at least one field to be filled;

[0053] A3. Determine reference product feature values ​​from the product information of the products to be purchased that correspond to the product feature information of each of the at least one field to be filled in;

[0054] A4. Perform the following operations on the product reference feature value corresponding to the product feature information of each of the at least one pending item to obtain the target feature value of each of the at least one pending item:

[0055] A41. Obtain the target number of m reference feature values ​​corresponding to the target product feature information of the currently processed item to be filled;

[0056] A42. If the number of targets is greater than or equal to 2, then the target feature value is determined as the product feature value with the highest total matching score of the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the file information;

[0057] A43. If the number of targets is equal to 1, then the m product feature values ​​are determined to be the target feature values.

[0058] Among them, at least one field to be filled may include, but is not limited to, product name, product style number, product color, and product flavor. The product name field is the product name, the product style number field is the style number, the product color field is the color, and the product flavor field is the flavor.

[0059] In practice, the product feature information of a pending item can correspond to one or more product reference feature values, and the number of product reference feature values ​​is determined by the product information of the product to be purchased.

[0060] For example, if the product feature information for item A is flavor, and the product information for the product to be purchased includes flavors such as blueberry, apple, tomato, strawberry, and chocolate, then the product reference feature values ​​for the product to be purchased include five flavors: blueberry, apple, tomato, strawberry, and chocolate. The product feature value with the highest total matching score with the pet can be determined based on the pet's pet profile. If the total matching score for strawberry is the highest, then when generating the order, the feature value for item A to be filled in is strawberry.

[0061] For another example, if the product feature information for item A is flavor, and the product information for the product to be purchased only includes blueberry flavor, then the product reference feature value for the product to be purchased includes only blueberry flavor. Therefore, when generating the order, the feature value of item A to be filled in is blueberry flavor.

[0062] In this example, by extracting the product feature information of each of the at least one field to be filled in the order template, a reference product feature value corresponding to the product feature information of each of the at least one field to be filled is determined from the product information of the product to be purchased. Then, a target feature value for each field to be filled is determined from the reference product feature value. When there is more than one reference product feature value for a field to be filled, the product feature value with the highest total matching score with the pet is determined based on the pet profile and the target product feature information of the field to be filled, and thus the value to be filled in is determined. Therefore, filling in the feature value of the field to be filled based on the product information, the target product feature information of the field to be filled, and the pet profile of the pet can greatly improve the matching degree between the feature value of the field to be filled and the pet when generating an order.

[0063] In one possible implementation, determining the target feature value as the product feature value with the highest matching degree to the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the profile information may include, but is not limited to, performing the following operations for each of the m product reference feature values ​​based on the profile information and the product feature information:

[0064] B1. Determine the product feature type of the currently processed item to be filled based on the target product feature information;

[0065] B2. If the product feature category is clothing color, then based on the pet personality in the file information, determine the first matching score between the pet and the reference feature value of the currently processed product;

[0066] B3. Based on the pet's fur color in the file information, determine the second matching score between the pet and the reference feature value of the currently processed product;

[0067] B4. Based on the first matching score and the second matching score, determine the total matching score between the pet and the reference feature value of the currently processed product.

[0068] Specifically, the higher the match between a pet's personality and the product's reference feature value, the higher the first matching score; conversely, the lower the match, the lower the first matching score. Similarly, the higher the match between a pet's fur color and the product's reference feature value, the higher the second matching score; and vice versa. The more similar the pet's fur color is to the product's reference feature value, the higher the match; conversely, the less similar the pet's fur color is to the product's reference feature value, the lower the match.

[0069] In practice, the calculation method for the first matching score between pet personality and product reference feature value, as well as the second matching score between pet fur color and product reference feature value, can be preset as needed.

[0070] As can be seen in this example, when the product feature category to be filled in is clothing color, the server can determine the total matching score between the pet and the product reference feature value based on the pet's fur color and personality in the pet profile information. Since the product feature value with the highest total matching score is the value entered in the product field, and the total matching score is determined based on the pet's fur color and personality in the pet profile information, this embodiment of the application helps to ensure that the pet matches the value entered in the clothing color field of the order.

[0071] In one possible implementation, since claim materials may include multiple claim documents, and different claim documents have different levels of importance during the claim process, and the degree to which different claim documents are overlooked by the user may also vary, the claim documents can be sorted before being sent to the target user. The determination of the total matching score between the pet and the currently processed product reference feature value based on the first matching score and the second matching score may include, but is not limited to:

[0072] C1. Obtain the target user's color preference information for the product to be purchased;

[0073] C2. Based on the color preference information, determine the third matching score between the target user and the reference feature value of the currently processed product;

[0074] C3. Determine the total matching score based on the first matching score, the second matching score, and the third matching score.

[0075] The total matching score can be the sum of the first matching score, the second matching score, and the third matching score. Alternatively, the total matching score can be obtained by weighted calculation of the first matching score, the second matching score, and the third matching score.

[0076] Specifically, the more a user likes a product, the more its reference feature values ​​match the user's requirements; conversely, the more a user dislikes a product, the more its reference feature values ​​match the user's requirements. A user's color preference information can be directly obtained from the target user's user profile, or determined from the target user's historical product purchase records. For similar products to the product to be purchased, the more frequently a color is purchased, the more the user likes it.

[0077] If the product to be purchased includes yellow, white, black, and blue, then the product information includes these four colors. For example, if the user likes blue, then the third match score between blue and the target user is higher; if the user dislikes blue, then the third match score between blue and the target user is lower.

[0078] The calculation method for the third matching score between color tendency information and product reference feature values ​​can be preset as needed. The calculation method for determining the total matching score based on the first matching score, the second matching score, and the third matching score can also be preset as needed.

[0079] As can be seen in this example, when the product feature category to be filled in is clothing color, the server can determine the total matching score between the pet and the product reference feature value based on the pet's fur color, pet personality, and the target user's color preference information for the product to be purchased, according to the pet's profile information. Since the product feature value with the highest total matching score is the value entered in the product field, and the total matching score is determined based on the pet's fur color and pet personality in the pet's profile information, this embodiment of the application helps to ensure that both the pet and the user's preferences match the value entered in the clothing color field of the order.

[0080] In one possible implementation, after determining the product feature type of the currently processed item to be filled based on the target product feature information, the method further includes:

[0081] D1. If the product feature category is food flavor, then based on the pet flavor preferences in the file information, determine the fourth matching score between the target user and the currently processed product reference feature value;

[0082] D2. Based on the disease information in the file information, determine the fifth matching score between the pet and the reference feature value of the currently processed product;

[0083] D3. Based on the fourth matching score and the fifth matching score, determine the total matching score between the pet and the reference feature value of the currently processed product.

[0084] Specifically, the higher the match between pet's taste preferences and the product reference feature value, the higher the fourth matching score; conversely, the lower the match, the lower the fourth matching score. Similarly, the higher the match between disease information and the product reference feature value, the higher the fifth matching score; the lower the match, the lower the fifth matching score. The more complementary the disease information and the product reference feature value, the higher their match; conversely, the more contradictory they are, the lower their match. In other words, if the product reference feature value helps treat and / or alleviate the disease in the disease information, the higher the fifth matching score; conversely, if the product reference feature value aggravates the disease in the disease information, the lower the fifth matching score.

[0085] In practice, the calculation methods for the fourth matching score between pet taste preferences and product reference feature values, as well as the fifth matching score between disease information and product reference feature values, can be preset as needed. The calculation methods for the fourth and fifth matching scores and the total matching score of the currently processed product reference feature values ​​can also be preset as needed.

[0086] As can be seen in this example, when the product feature category to be filled in is food flavor, the server can determine the total matching score between the pet and the product reference feature value based on the pet's taste preferences and disease information in the pet's profile information. Since the product feature value with the highest total matching score is the value entered in the product feature category, and the total matching score is determined based on the pet's taste preferences and disease information in the pet's profile information, this embodiment of the application helps to ensure that the pet matches the value entered in the food flavor field of the order.

[0087] Please see Figure 3 , Figure 3This application provides a flowchart illustrating another method for pushing pet product orders.

[0088] like Figure 3 As shown, this method can be applied to a server, and the method includes:

[0089] 301. Obtain the product information of the pet's items to be purchased, and obtain the pet's nose print image;

[0090] 302. Obtain the file information corresponding to the pet based on the nose print image;

[0091] 303. Determine the order template based on the goods to be purchased;

[0092] 304. Identify at least one field to be filled in the order template;

[0093] 305. Obtain the product feature information of each of the at least one field to be filled;

[0094] 306. Determine reference product feature values ​​from the product information of the goods to be purchased, corresponding to the product feature information of each of the at least one field to be filled in;

[0095] 307. Perform the following operations on the product reference feature value corresponding to the product feature information of each of the at least one pending item to obtain the target feature value of each of the at least one pending item:

[0096] 3071. Obtain the target number of m reference feature values ​​corresponding to the target product feature information of the currently processed item to be filled;

[0097] 3072. If the number of targets is greater than or equal to 2, then the target feature value is determined as the product feature value with the highest total matching score of the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the file information;

[0098] 3073. If the number of targets is equal to 1, then the m product feature values ​​are determined to be the target feature values;

[0099] 308. Fill the order data into the order template to obtain the target order for the goods to be purchased;

[0100] 309. Send the target order to the target user corresponding to the pet.

[0101] in, Figure 3 Steps 301-309 refer to the above-mentioned steps. Figure 2 The descriptions of steps S201-S206 are not repeated here.

[0102] As can be seen in this example, the server can obtain the product information of the pet's items to be purchased, as well as the pet's nose print image. Based on the nose print image, it retrieves the corresponding profile information for the pet. It determines the order template based on the items to be purchased, and based on the order template and profile information, it identifies the order data corresponding to the order template from the product information of the items to be purchased. The order data is then filled into the order template to obtain the target order for the items to be purchased, and the target order is sent to the target user corresponding to the pet. Therefore, the server can fill in the order for the pet's items to be purchased based on the pet's product information and nose print image, and push it to the user. This eliminates the need for the user to fill in order data item by item, improving the intelligence of pet product order push and enhancing the user experience.

[0103] The pet product order push method provided in this application embodiment can be applied to pet product order push scenarios when users purchase pet items online. For example... Figure 4A As shown, in this scenario, users can purchase items for their pet dogs using mobile phones or other electronic devices. Before purchasing the necessary pet items, users need to create a pet profile for their dog and send this profile to the server for storage. Users can use a shopping app on their phone to scan the dog's nose print using the phone's camera to obtain a nose print image. Users can also select the pet supplies they want to buy on their phone. Then, the user sends the nose print image and the unique identifier of the pet supplies to the server. The server selects the pet's profile based on the nose print image, selects the supply information based on the unique identifier, selects an order template based on the unique identifier, and determines the order data corresponding to the order template based on the pet profile, order template, and supply information. The server automatically fills the order data into the order template, generates the order, and sends the order to the user's mobile phone. When users purchase pet supplies online, the server can fill in the order information for the pet's purchases based on the pet's product information and nose print image, and then push it to the user. This eliminates the need for users to fill in order data item by item, thereby improving the intelligence of pet product order push and enhancing the user experience.

[0104] The pet product order push method provided in this application embodiment can be applied to scenarios where pet product orders are pushed to users when they are shopping for pet supplies in a supermarket. For example... Figure 4BAs shown, in this scenario, users can purchase items for their pet dogs using a shopping device provided by a supermarket. Before purchasing the necessary pet items, users need to create a pet profile for their dog and send this profile to the server for storage. Users can use the shopping app on the device to activate the device's camera to scan the dog's nose print to obtain a nose print image. Users can also select the pet supplies they want to buy on the shopping device. The shopping device then sends the nose print image and the unique identifier of the pet supplies to the server. The server selects the pet's profile based on the nose print image, selects the pet supplies information based on the unique identifier, selects an order template based on the unique identifier, and determines the order data corresponding to the order template based on the pet profile, order template, and supplies information. The server automatically fills the order data into the order template, generates the order, and sends the order to the shopping device. When users purchase pet supplies online, the server can fill in the order information for the pet's purchases based on the pet's product information and nose print image, and then push it to the user. This eliminates the need for users to fill in order data item by item, thereby improving the intelligence of pet product order push and enhancing the user experience.

[0105] Figure 4A , 4B The example used here is a pet dog; it is just an illustration. Of course, pets can include other pets that can be used for nose print recognition.

[0106] For examples consistent with the above embodiments, please refer to... Figure 5 , Figure 5 A schematic diagram of a server structure provided in an embodiment of this application is shown in the figure. It includes a processor, an input device, an output device, and a memory. The processor, input device, output device, and memory are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call one or more programs containing the program instructions. The one or more programs include instructions for performing the following steps.

[0107] Obtain product information of the pet's intended purchase items, and obtain the pet's nose print image;

[0108] Obtain the file information corresponding to the pet based on the nose print image;

[0109] Determine the order template based on the items to be purchased;

[0110] Based on the order template and the file information, the order data corresponding to the order template is determined from the product information of the goods to be purchased;

[0111] The order data is entered into the order template to obtain the target order for the goods to be purchased.

[0112] Send the target order to the target user corresponding to the pet.

[0113] In one possible implementation, regarding the step of determining the order data corresponding to the order template from the product information of the goods to be purchased based on the order template and the file information, the instructions in the above one or more programs are specifically used for:

[0114] Identify at least one field to be filled in the order template;

[0115] Obtain the product feature information for each of the at least one fields to be filled;

[0116] Determine reference product feature values ​​from the product information of the products to be purchased, which correspond to the product feature information of each of the at least one field to be filled in;

[0117] Perform the following operations on the product reference feature value corresponding to the product feature information of each of the at least one pending item to obtain the target feature value of each of the at least one pending item:

[0118] Obtain the target number of m reference feature values ​​corresponding to the target product feature information of the currently processed item to be filled;

[0119] If the number of targets is greater than or equal to 2, then the target feature value is determined as the product feature value with the highest total matching score of the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the file information;

[0120] If the number of targets is equal to 1, then the m product feature values ​​are determined to be the target feature values.

[0121] In one possible implementation, regarding determining the target feature value as the product feature value with the highest matching degree to the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the profile information, the instructions in one or more of the above-mentioned programs are specifically used to perform the following operations for each of the m product reference feature values ​​based on the profile information and the product feature information:

[0122] The product feature type of the currently processed field to be filled is determined based on the target product feature information;

[0123] If the product feature category is clothing color, then based on the pet personality in the file information, determine the first matching score between the pet and the reference feature value of the currently processed product;

[0124] Based on the pet's fur color in the file information, a second matching score is determined between the pet and the reference feature value of the currently processed product;

[0125] Based on the first matching score and the second matching score, the total matching score between the pet and the reference feature value of the currently processed product is determined.

[0126] In one possible implementation, regarding the determination of the total matching score between the pet and the currently processed product reference feature value based on the first matching score and the second matching score, the instructions in the above one or more procedures are specifically used for:

[0127] Obtain the target user's color preference information for the product to be purchased;

[0128] Based on the color preference information, a third matching score is determined between the target user and the reference feature value of the currently processed product;

[0129] The total matching score is determined based on the first matching score, the second matching score, and the third matching score.

[0130] In one possible implementation, the above one or more programs may further include instructions for performing the following steps;

[0131] After determining the product feature type of the currently processed item to be filled based on the target product feature information, the method further includes:

[0132] If the product feature category is food flavor, then based on the pet flavor preferences in the file information, determine the fourth matching score between the target user and the currently processed product reference feature value;

[0133] Based on the disease information in the file information, determine the fifth matching score between the pet and the reference feature value of the currently processed product;

[0134] Based on the fourth matching score and the fifth matching score, the total matching score between the pet and the reference feature value of the currently processed product is determined.

[0135] The above mainly describes the solutions of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, the terminal includes the corresponding hardware structure and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0136] This application embodiment can divide the terminal into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0137] For those consistent with the above, please refer to Figure 6 , Figure 6 This application provides a schematic diagram of a pet product order push device. Figure 6 As shown, the pet product order push device 600 includes:

[0138] The first acquisition unit 601 is used to acquire product information of the pet's purchase items and to acquire the pet's nose print image.

[0139] The second acquisition unit 602 is used to acquire file information corresponding to the pet based on the nose print image;

[0140] The first determining unit 603 is used to determine an order template based on the goods to be purchased;

[0141] The second determining unit 604 is used to determine the order data corresponding to the order template from the product information of the goods to be purchased based on the order template and the file information;

[0142] The order generation unit 605 is used to fill the order data into the order template to obtain the target order for the goods to be purchased.

[0143] Sending unit 606 is used to send the target order to the target user corresponding to the pet.

[0144] The pet product order push device 600 may further include a storage unit 607 for storing program code and data of the electronic device. The storage unit 607 may be a memory.

[0145] In one possible implementation, in determining the order data corresponding to the order template from the product information of the goods to be purchased based on the order template and the file information, the second determining unit 604 is specifically used for:

[0146] Identify at least one field to be filled in the order template;

[0147] Obtain the product feature information for each of the at least one fields to be filled;

[0148] Determine reference product feature values ​​from the product information of the products to be purchased, which correspond to the product feature information of each of the at least one field to be filled in;

[0149] Perform the following operations on the product reference feature value corresponding to the product feature information of each of the at least one pending item to obtain the target feature value of each of the at least one pending item:

[0150] Obtain the target number of m reference feature values ​​corresponding to the target product feature information of the currently processed item to be filled;

[0151] If the number of targets is greater than or equal to 2, then the target feature value is determined as the product feature value with the highest total matching score of the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the file information;

[0152] If the number of targets is equal to 1, then the m product feature values ​​are determined to be the target feature values.

[0153] In one possible implementation, in determining the target feature value as the product feature value with the highest matching degree to the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the profile information, the second determining unit 604 is specifically configured to perform the following operations for each of the m product reference feature values ​​based on the profile information and the product feature information:

[0154] The product feature type of the currently processed field to be filled is determined based on the target product feature information;

[0155] If the product feature category is clothing color, then based on the pet personality in the file information, determine the first matching score between the pet and the reference feature value of the currently processed product;

[0156] Based on the pet's fur color in the file information, a second matching score is determined between the pet and the reference feature value of the currently processed product;

[0157] Based on the first matching score and the second matching score, the total matching score between the pet and the reference feature value of the currently processed product is determined.

[0158] In one possible implementation, regarding the determination of the total matching score between the pet and the currently processed product reference feature value based on the first matching score and the second matching score, the second determining unit 604 is specifically used for:

[0159] Obtain the target user's color preference information for the product to be purchased;

[0160] Based on the color preference information, a third matching score is determined between the target user and the reference feature value of the currently processed product;

[0161] The total matching score is determined based on the first matching score, the second matching score, and the third matching score.

[0162] In one possible implementation, the second determining unit 604 is further configured to: after determining the product feature type of the currently processed item to be filled based on the target product feature information, if the product feature type is food flavor, then determine the fourth matching score between the target user and the currently processed product reference feature value based on the pet taste preferences in the file information;

[0163] Based on the disease information in the file information, determine the fifth matching score between the pet and the reference feature value of the currently processed product;

[0164] Based on the fourth matching score and the fifth matching score, the total matching score between the pet and the reference feature value of the currently processed product is determined.

[0165] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the pet product order push methods described in the above method embodiments.

[0166] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps of any of the pet product order push methods described in the above method embodiments.

[0167] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0168] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0169] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0170] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0171] Furthermore, the functional units in the various embodiments of the application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0172] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, 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. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0173] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory, a random access memory, a magnetic disk, or an optical disk, etc.

[0174] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for pushing pet product orders, characterized in that, The method includes: Obtain product information of the pet's intended purchase items, and obtain the pet's nose print image; Obtain the file information corresponding to the pet based on the nose print image; Determine the order template based on the items to be purchased; Based on the order template and the file information, the order data corresponding to the order template is determined from the product information of the goods to be purchased; The order data is entered into the order template to obtain the target order for the goods to be purchased. Send the target order to the target user corresponding to the pet; The step of determining the order data corresponding to the order template from the product information of the goods to be purchased based on the order template and the file information includes: determining at least one field to be filled in the order template; Obtain the product feature information for each of the at least one fields to be filled; Determine reference product feature values ​​from the product information of the products to be purchased, which correspond to the product feature information of each of the at least one field to be filled in; Perform the following operations on the product reference feature value corresponding to the product feature information of each of the at least one pending item to obtain the target feature value of each of the at least one pending item: Obtain the target number of m reference feature values ​​corresponding to the target product feature information of the currently processed item to be filled; If the number of targets is equal to 1, then the m reference feature values ​​of the products are determined to be the target feature values.

2. The method according to claim 1, characterized in that, The method further includes: If the number of targets is greater than or equal to 2, then the target feature value is determined as the product feature value with the highest total matching score among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the file information.

3. The method according to claim 2, characterized in that, The step of determining the target feature value as the product feature value with the highest total matching score for the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the profile information includes performing the following operations for each of the m product reference feature values ​​based on the profile information and the product feature information: The product feature type of the currently processed field to be filled is determined based on the target product feature information; If the product feature category is clothing color, then based on the pet personality in the file information, determine the first matching score between the pet and the reference feature value of the currently processed product; Based on the pet's fur color in the file information, a second matching score is determined between the pet and the reference feature value of the currently processed product; Based on the first matching score and the second matching score, the total matching score between the pet and the reference feature value of the currently processed product is determined.

4. The method according to claim 3, characterized in that, The step of determining the total matching score between the pet and the currently processed product reference feature value based on the first matching score and the second matching score includes: Obtain the target user's color preference information for the product to be purchased; Based on the color preference information, a third matching score is determined between the target user and the reference feature value of the currently processed product; The total matching score is determined based on the first matching score, the second matching score, and the third matching score.

5. The method according to claim 3, characterized in that, After determining the product feature type of the currently processed item to be filled based on the target product feature information, the method further includes: If the product feature category is food flavor, then based on the pet flavor preferences in the file information, determine the fourth matching score between the target user and the currently processed product reference feature value; Based on the disease information in the file information, determine the fifth matching score between the pet and the reference feature value of the currently processed product; Based on the fourth matching score and the fifth matching score, the total matching score between the pet and the reference feature value of the currently processed product is determined.

6. A pet product order push device, characterized in that, The device includes: The first acquisition unit is used to acquire product information of the pet's purchase items and to acquire the pet's nose print image. The second acquisition unit is used to acquire file information corresponding to the pet based on the nose print image; The first determining unit is used to determine an order template based on the goods to be purchased; The second determining unit is used to determine the order data corresponding to the order template from the product information of the goods to be purchased based on the order template and the file information; An order generation unit is used to fill the order data into the order template to obtain the target order for the goods to be purchased. Sending unit, used to send the target order to the target user corresponding to the pet; The step of determining the order data corresponding to the order template from the product information of the goods to be purchased based on the order template and the file information includes: determining at least one field to be filled in the order template; obtaining product feature information for each of the at least one field to be filled; determining reference product feature values ​​corresponding to the product feature information of each of the at least one field to be filled from the product information of the goods to be purchased; and performing the following operations on the reference product feature values ​​corresponding to the product feature information of each of the at least one field to be filled to obtain the target feature value of each of the at least one field to be filled: obtaining the target number of m reference product feature values ​​corresponding to the target product feature information of the currently processed field to be filled; if the target number is equal to 1, then determining the m reference product feature values ​​as the target feature value.

7. The apparatus according to claim 6, characterized in that, The second determining unit is further configured to: If the number of targets is greater than or equal to 2, then the target feature value is determined as the product feature value with the highest total matching score among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the file information.

8. The apparatus according to claim 7, characterized in that, In determining the target feature value as the product feature value with the highest matching degree to the pet among the m product reference feature values ​​based on the target product feature information of the currently processed item to be filled and the file information, the second determining unit is specifically used to perform the following operations for each of the m product reference feature values ​​based on the file information and the product feature information: The product feature type of the currently processed field to be filled is determined based on the target product feature information; If the product feature category is clothing color, then based on the pet personality in the file information, determine the first matching score between the pet and the reference feature value of the currently processed product; Based on the pet's fur color in the file information, a second matching score is determined between the pet and the reference feature value of the currently processed product; Based on the first matching score and the second matching score, the total matching score between the pet and the reference feature value of the currently processed product is determined.

9. A server, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to invoke the program instructions to perform the method as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-5.

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