Clothing recommendation method, device, equipment and storage medium

Abstract

The embodiments of the present invention belong to the field of data processing technology, and specifically relate to a clothing recommendation method, device, equipment and storage medium. The present invention aims to solve the technical problem that the efficiency of online shopping in the prior art is low and the online shopping experience of users is poor. The method includes: obtaining attribute information of at least one piece of clothing to be washed in a washing machine, clustering the attribute information of the clothing to determine clothing attribute information corresponding to at least one target user, and pushing clothing information that matches the clothing attribute information corresponding to the target user according to a preset push strategy. It enables users to view purchase information suitable for themselves in a timely manner, improves the efficiency of online shopping, and thus improves the user's online shopping experience.

Description

Technical Field

[0001] The present invention belongs to the field of data processing, and in particular relates to a clothing recommendation method, device, equipment and storage medium. Background Art

[0002] With the continuous development of mobile Internet, online shopping has become a popular trend. In particular, all kinds of clothing are the main component of online shopping.

[0003] Although online shopping allows people to complete their shopping without leaving home, which brings convenience to people, people will only open the corresponding shopping application to make corresponding shopping when they have the need to shop online. In addition, when shopping online, they need to select clothes, and after selecting, they need to check whether there is the color, size and other information they like before they can successfully complete the shopping, which makes online shopping less efficient and leads to a poor online shopping experience for users.

[0004] Accordingly, the art needs a clothing recommendation solution to solve the above problems. Summary of the invention

[0005] The present invention provides a clothing recommendation method, device, equipment and storage medium, which solve the technical problem in the prior art that low online shopping efficiency leads to poor online shopping experience for users.

[0006] In a first aspect, an embodiment of the present invention provides a clothing recommendation method, the method comprising:

[0007] Obtaining attribute information of at least one piece of clothing to be washed in the washing machine;

[0008] performing clustering processing on the attribute information of the clothing to determine the attribute information of the clothing corresponding to at least one target user;

[0009] The clothing information matching the clothing attribute information corresponding to the target user is pushed according to a preset push strategy.

[0010] In an optional technical solution of the above clothing recommendation method, the step of obtaining attribute information of at least one piece of clothing to be washed in the washing machine includes:

[0011] If a washing machine start signal is detected, a visual sensor is used to collect an image including at least one piece of clothing;

[0012] Detecting clothing labels in the image to obtain clothing label images;

[0013] Character recognition is performed on the clothing label image to obtain attribute information of the clothing.

[0014] In an optional technical solution of the above clothing recommendation method, the step of obtaining attribute information of at least one piece of clothing to be washed in the washing machine includes:

[0015] If a washing machine start signal is detected, the reader is controlled to read clothing attribute information stored in an electronic tag carried by at least one piece of clothing;

[0016] The clothing attribute information is obtained from the reader.

[0017] In an optional technical solution of the above clothing recommendation method, clustering the attribute information of the clothing to determine the clothing attribute information corresponding to at least one target user includes:

[0018] Inputting the attribute information of the clothing into a preset clustering model;

[0019] The attribute information of the clothing is clustered using the preset clustering model, and clothing attribute information corresponding to at least one target user is output.

[0020] In the optional technical solution of the above clothing recommendation method, the pushing of clothing information matching the clothing attribute information corresponding to the target user according to a preset push strategy includes:

[0021] Determine the number of different clothes corresponding to the target user among the clothes to be washed in the washing machine within a preset time period;

[0022] Determining a push time interval for the clothing information of the corresponding target user according to the number of the different clothing items;

[0023] Clothing information matching the clothing attribute information corresponding to the target user is pushed according to the push time interval.

[0024] In an optional technical solution of the above clothing recommendation method, the determining the number of different clothes corresponding to the target user in the clothes to be washed in the washing machine within a preset time period includes:

[0025] Acquire attribute information of a plurality of pieces of clothing corresponding to the target user from the clothing to be washed in the washing machine within the preset time period;

[0026] The attribute information of the multiple pieces of clothing corresponding to the target user is compared to determine the number of different pieces of clothing corresponding to the target user.

[0027] In the optional technical solution of the above clothing recommendation method, after pushing the clothing information matching the clothing attribute information corresponding to the target user according to the preset push strategy, it also includes:

[0028] Obtain the clothing information corresponding to the target user who has purchased;

[0029] Adjusting the clothing attribute information corresponding to the target user according to the clothing information corresponding to the purchased target user;

[0030] The preset clustering model is optimized according to the adjusted clothing attribute information corresponding to the target user.

[0031] In an optional technical solution of the above clothing recommendation method, after clustering the attribute information of the clothing to determine the clothing attribute information corresponding to at least one target user, the method further includes:

[0032] Pushing washing and care data that matches the clothing attribute information corresponding to the target user.

[0033] In a second aspect, an embodiment of the present invention provides a clothing recommendation device, the device comprising:

[0034] Memory, processor;

[0035] Memory; Memory for storing instructions executable by the processor;

[0036] The processor is configured to execute the method according to any one of claims 1 to 8.

[0037] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method as described in any one of the first aspects.

[0038] It will be understood by those skilled in the art that, in the clothing recommendation method, device, equipment and storage medium of the present invention, the method obtains attribute information of at least one piece of clothing to be washed in the washing machine, clusters the attribute information of the clothing to determine clothing attribute information corresponding to at least one target user, and pushes clothing information matching the clothing attribute information corresponding to the target user according to a preset push strategy. Since the clothing attribute information of the target user is determined and clothing information matching the clothing attribute information is pushed to the user, the user can view purchase information suitable for him / her in a timely manner, thereby improving the efficiency of online shopping and thus improving the user's online shopping experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The following describes the optional implementation of the clothing recommendation method, device, equipment and storage medium of the present invention with reference to the accompanying drawings.

[0040] Figure 1 A diagram of an application scenario of the clothing recommendation method provided by an embodiment of the present invention;

[0041] Figure 2A schematic diagram of a flow chart of a clothing recommendation method provided by an embodiment of the present invention;

[0042] Figure 3 A schematic diagram of a flow chart of a clothing recommendation method provided by another embodiment of the present invention;

[0043] Figure 4 A schematic diagram of a flow chart of a clothing recommendation method provided by another embodiment of the present invention;

[0044] Figure 5 A schematic diagram of the structure of a clothing recommendation device provided by an embodiment of the present invention;

[0045] Figure 6 A schematic diagram of the hardware structure of a clothing recommendation device provided in one embodiment of the present invention.

[0046] The above drawings have shown clear embodiments of the present invention, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present invention in any way, but to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0047] It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention. Those skilled in the art may make adjustments to them as needed to adapt to specific application scenarios.

[0048] First, the application scenarios of the clothing recommendation method provided by the embodiment of the present invention are introduced. Figure 1 As shown, the application scenario of the embodiment of the present invention includes: an electronic device and a washing machine. The electronic device is connected to the washing machine for communication. The electronic device may include an application client of the clothing recommendation method. The application client has an interactive interface with the user. The interactive interface may include: shopping options. After clustering the attribute information of the washed clothes, the washing machine can generate clothing information that matches the clothing attribute information according to the clothing attributes of the target user obtained after the clustering process, and push the clothing information to the application client of the electronic device of the target user. The application client displays the pushed clothing information suitable for the target user to the user in response to the instruction input by the user according to the reminder message pushed by the clothing information, so that the user can choose to buy. Since the pushed clothing information is determined according to the clothing attribute information of the target user, it better meets the needs of the target user, effectively improves the efficiency of purchasing clothing, and improves the user's online shopping experience.

[0049] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0050] Figure 2 FIG. 1 is a flow chart of a clothing recommendation method provided by an embodiment of the present invention, as shown in FIG. Figure 2 As shown, the execution subject of the clothing recommendation method provided in this embodiment is a device with independent computing and processing capabilities, such as a washing machine. The clothing recommendation method provided in this embodiment includes the following steps:

[0051] 201. Obtain attribute information of at least one piece of clothing to be washed in a washing machine.

[0052] In this embodiment, there are multiple ways to obtain the attribute information of at least one piece of clothing to be washed in the washing machine.

[0053] In one feasible manner, the image of the clothing label can be captured by a visual sensor arranged on the washing machine to obtain the attribute information of the clothing, that is, the attribute information of at least one piece of clothing to be washed in the washing machine is obtained, including: if a washing machine start signal is detected, using the visual sensor to capture an image including at least one piece of clothing; detecting the clothing label in the image to obtain a clothing label image; and performing character recognition on the clothing label image to obtain the attribute information of the clothing.

[0054] In practical applications, the start signal of the washing machine may be a start signal or a selection signal of a washing program of the washing machine, or may be a signal for opening or closing a door of the washing machine, which is not limited in this embodiment.

[0055] In another feasible manner, the electronic tag carried by the washed clothes can be identified by a reader arranged on the washing machine to obtain the attribute information of the clothes, that is, the attribute information of at least one piece of clothing to be washed in the washing machine is obtained, including: if a washing machine start signal is detected, controlling the reader to read the clothing attribute information stored in the electronic tag carried by at least one piece of clothing; and obtaining the clothing attribute information from the reader.

[0056] 202. Perform clustering processing on the attribute information of the clothing to determine clothing attribute information corresponding to at least one target user.

[0057] Among them, the target user is the user to whom clothing is recommended.

[0058] In this embodiment, the clothing attribute information may include: clothing type, clothing color, clothing size, clothing material, clothing brand, etc., which is not limited in this embodiment.

[0059] In this embodiment, taking a family as an example, if the family is a family of three, then possible family members include middle-aged men, middle-aged women and children. During the use of the washing machine, the clothes of the three members may be washed simultaneously or in batches. After the clothes are put into the washing machine, the washing machine can obtain the attribute information of the clothes by performing radio frequency identification (RFID tags) or image recognition on the tags of the clothes. The washing machine can collect information on all washed clothes in each washing task. After multiple washing tasks, the attribute information of multiple clothes can be collected. After the attribute information of these clothes is processed by example, the clustering results can be obtained:

[0060] Middle-aged men: Male: top size 170, bottom size 30, suit, Heilan Home;

[0061] Women: tops size 165, bottoms size 28, dresses, HM;

[0062] Boys: Tops size 140, bottoms size 140, sportswear, balabala.

[0063] It is understandable that if each family member purchases clothes from multiple brands, the clustering results may include information such as clothing size and clothing type corresponding to each brand.

[0064] Optionally, in actual applications, the attribute information of the clothing is clustered to determine the clothing attribute information corresponding to at least one target user, including: inputting the attribute information of the clothing into a preset clustering model; clustering the attribute information of the clothing through the preset clustering model, and outputting the clothing attribute information corresponding to at least one target user.

[0065] 203. Push clothing information that matches the clothing attribute information corresponding to the target user according to a preset push strategy.

[0066] There may be multiple push strategies adopted in this embodiment, which can be set according to actual needs, and this embodiment does not limit this.

[0067] In one implementable manner, the push time interval can be determined according to the number of clothes owned by the target user within a certain period of time, and the clothing information can be pushed at the time interval. Specifically, the pushing of clothing information matching the clothing attribute information corresponding to the target user according to a preset push strategy includes: determining the number of different clothes corresponding to the target user among the clothes to be washed in the washing machine within a preset time period; determining the push time interval of the clothing information corresponding to the target user according to the number of different clothes; and pushing the clothing information matching the clothing attribute information corresponding to the target user according to the push time interval.

[0068] Optionally, in actual application, the determination of the number of different clothes corresponding to the target user in the clothes to be washed in the washing machine within the preset time period includes: obtaining attribute information of multiple clothes corresponding to the target user in the clothes to be washed in the washing machine within the preset time period; comparing the attribute information of the multiple clothes corresponding to the target user to determine the number of different clothes corresponding to the target user. For example, the clothes washed by the washing machine include multiple shirts of the target user. By comparing the size, brand and color of the shirts, it is possible to distinguish how many shirts the user specifically owns. Of course, the user may also buy two clothes of the same brand and model at the same time. In this case, the obtained images of the clothes can be compared in detail to distinguish them according to the characteristics of the clothes themselves, such as the button positions or quantities of the two shirts are slightly different, or the newness and oldness are different.

[0069] For example, if it is detected that a middle-aged man in the family only washes two different kinds of clothes in a week, the frequency of pushing the suitable clothing information to the man can be set to once a month; if it is detected that a middle-aged woman in the family washes five different kinds of clothes in a week, the frequency of pushing the suitable clothing information to the woman can be set to once a week.

[0070] In another possible implementation, the push time can be determined according to the target user's demand for brand and style. Specifically, the push of clothing information matching the clothing attribute information corresponding to the target user according to the preset push strategy includes: determining different clothing styles corresponding to the target user among the clothing to be washed in the washing machine within a preset time period; determining the push time interval of the clothing information corresponding to the target user according to the different clothing styles; and pushing the clothing information matching the clothing attribute information corresponding to the target user according to the push time interval.

[0071] In actual applications, clothing styles may include seasonal new styles, classic styles, and the like. The push time may be determined based on whether the target user's clothing included in the laundry of the washing machine is seasonal new style. If it is seasonal new style, clothing information may be pushed when the brand clothing favored by the target user launches seasonal new styles. If it is classic style, clothing recommendation information may be pushed according to a preset time interval.

[0072] The clothing recommendation method provided in the present embodiment obtains attribute information of at least one piece of clothing to be washed in the washing machine, clusters the attribute information of the clothing to determine clothing attribute information corresponding to at least one target user, and pushes clothing information matching the clothing attribute information corresponding to the target user according to a preset push strategy. Since the clothing attribute information of the target user is determined and clothing information matching the clothing attribute information is pushed to the user, the user can view purchase information suitable for him / her in a timely manner, thereby improving the efficiency of online shopping and thus improving the user's online shopping experience.

[0073] Figure 3 A schematic diagram of a flow chart of a clothing recommendation method provided by another embodiment of the present invention is shown in FIG. Figure 3 As shown, based on the above embodiment, for example Figure 2 Based on the embodiment shown, this embodiment describes the clustering process in detail and adds optimization measures for the clustering process. The clothing recommendation method provided in this embodiment includes the following steps:

[0074] 301. Obtain attribute information of at least one piece of clothing to be washed in a washing machine.

[0075] Step 301 in this embodiment is similar to step 201 in the above embodiment and will not be described again here.

[0076] 302. Input the attribute information of the clothing into a preset clustering model.

[0077] 303. Cluster the attribute information of the clothing using the preset clustering model, and output clothing attribute information corresponding to at least one target user.

[0078] In this embodiment, taking a family as an example, attribute information such as clothing type, clothing brand, clothing size, clothing color, etc. of each family member's clothing is input into a preset clustering model, and the preset clustering model clusters the attribute information of clothing to classify the clothing and obtain the clothing preferences of each family member, such as applicable size, preferred brand, clothing type, etc. Therefore, clothing can be accurately pushed according to the clothing preferences of each family member.

[0079] 304. Push clothing information that matches the clothing attribute information corresponding to the target user according to a preset push strategy.

[0080] Step 304 in this embodiment is similar to step 203 in the above embodiment and will not be described again here.

[0081] 305. Obtain the clothing information corresponding to the target user that has been purchased.

[0082] 306. Adjust the clothing attribute information corresponding to the target user according to the clothing information corresponding to the target user that has been purchased.

[0083] 307. Optimize the preset clustering model according to the adjusted clothing attribute information corresponding to the target user.

[0084] Taking the family as an example, in actual applications, each family member may have changes in body shape. For example, after a lady in the family becomes pregnant, the type of clothing may change to maternity wear, the size of clothing may increase in stages, and more brands may need to be purchased for maternity brands. For children in the family, since they are in the growth period, their height will continue to increase, and the size of clothing will need to increase regularly. Therefore, according to the information of each family member purchasing clothing, the clothing attribute information corresponding to the target user can be adjusted, and the preset clustering model can be optimized according to the clothing attribute information, so that the optimized clustering model can obtain more accurate clustering results, so as to make more accurate recommendations to the target user and improve the user's shopping efficiency and shopping experience.

[0085] The clothing recommendation method provided in the present embodiment can obtain clothing attribute information corresponding to at least one target user by clustering clothing attribute information using a preset clustering model, and in a later stage, by analyzing the clothing information purchased by the target user and adjusting the clothing attribute information corresponding to the target user according to the analysis result, and optimizing the preset clustering model through the adjusted clothing attribute information corresponding to the target user, the result of subsequent clustering processing of the clothing attribute information can be made more accurate, thereby making more accurate clothing recommendations to users and improving the user's shopping experience.

[0086] Figure 4 A schematic diagram of a flow chart of a clothing recommendation method provided by another embodiment of the present invention is shown in FIG. Figure 4 As shown, based on the above embodiment, for example Figure 2 On the basis of the embodiment shown, this embodiment adds the push of washing and care data of the target user to ensure that the target user washes and cares for the clothes correctly. The clothing recommendation method provided in this embodiment includes the following steps:

[0087] 401. Obtain attribute information of at least one piece of clothing to be washed in the washing machine.

[0088] 402. Perform clustering processing on the attribute information of the clothing to determine clothing attribute information corresponding to at least one target user.

[0089] 403. Push clothing information that matches the clothing attribute information corresponding to the target user according to a preset push strategy.

[0090] Steps 401 to 403 in this embodiment are similar to steps 201 to 203 in the above embodiment, and are not described again here.

[0091] 404. Pushing washing and care data that matches the clothing attribute information corresponding to the target user.

[0092] In this embodiment, the washing and care data may include information such as applicable detergents and washing types that match the washing machine.

[0093] In actual applications, although most clothes carry labels that introduce washing and care matters, users need to actively look for them, and the washing and care contents on the labels are relatively simple, only introducing information such as washing temperature. In this embodiment, after obtaining the clothing attribute information corresponding to the target user through clustering processing, the washing and care data matching the clothing attribute information of the target user can be accurately pushed to extend the use period of the clothing.

[0094] The clothing recommendation method provided in this embodiment can enable the target user to wash and care for the clothes reasonably, increase the number of times the clothes are worn and washed, and save expenses for the user by pushing the clothing attribute information corresponding to the target user and the matching washing and care data to the target user.

[0095] Figure 5 Schematic diagram of the structure of a clothing recommendation device provided by an embodiment of the present invention. Figure 5 As shown, the clothing recommendation device 50 includes:

[0096] An acquisition module 501 is used to acquire attribute information of at least one piece of clothing to be washed in the washing machine;

[0097] A processing module 502 is used to perform clustering processing on the attribute information of the clothing to determine the attribute information of the clothing corresponding to at least one target user;

[0098] The push module 503 is used to push clothing information matching the clothing attribute information corresponding to the target user according to a preset push strategy.

[0099] The clothing recommendation device provided in this embodiment obtains the attribute information of at least one piece of clothing to be washed in the washing machine through the acquisition module 501, and the processing module 502 performs clustering processing on the attribute information of the clothing to determine the clothing attribute information corresponding to at least one target user. The push module 503 pushes the clothing information matching the clothing attribute information corresponding to the target user according to the preset push strategy. Since the clothing attribute information of the target user is determined and the clothing information matching the clothing attribute information is pushed to the user, the user can view the purchase information suitable for him / her in time, which improves the efficiency of online shopping and thus improves the user's online shopping experience.

[0100] Optionally, the acquisition module 501 is specifically used for:

[0101] If a washing machine start signal is detected, a visual sensor is used to collect an image including at least one piece of clothing;

[0102] Detecting clothing labels in the image to obtain clothing label images;

[0103] Character recognition is performed on the clothing label image to obtain attribute information of the clothing.

[0104] Optionally, the acquisition module 501 is specifically used for:

[0105] If a washing machine start signal is detected, the reader is controlled to read clothing attribute information stored in an electronic tag carried by at least one piece of clothing;

[0106] The clothing attribute information is obtained from the reader.

[0107] Optionally, the processing module 502 is specifically configured to:

[0108] Inputting the attribute information of the clothing into a preset clustering model;

[0109] The attribute information of the clothing is clustered using the preset clustering model, and clothing attribute information corresponding to at least one target user is output.

[0110] Optionally, the push module 503 is specifically used for:

[0111] Determine the number of different clothes corresponding to the target user among the clothes to be washed in the washing machine within a preset time period;

[0112] Determining a push time interval for the clothing information of the corresponding target user according to the number of the different clothing items;

[0113] Clothing information matching the clothing attribute information corresponding to the target user is pushed according to the push time interval.

[0114] Optionally, the push module 503 is specifically used for:

[0115] Acquire attribute information of a plurality of pieces of clothing corresponding to the target user from the clothing to be washed in the washing machine within the preset time period;

[0116] The attribute information of the multiple pieces of clothing corresponding to the target user is compared to determine the number of different pieces of clothing corresponding to the target user.

[0117] Optionally, the device 50 also includes: an optimization module, used to obtain clothing information corresponding to the target user who has purchased; adjust the clothing attribute information corresponding to the target user according to the clothing information corresponding to the target user who has purchased; and optimize the preset clustering model according to the adjusted clothing attribute information corresponding to the target user.

[0118] Optionally, the device 50 further includes: a washing and care data pushing module, configured to push washing and care data matching the clothing attribute information corresponding to the target user.

[0119] The clothing recommendation device provided in the embodiment of the present invention can be used to execute the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0120] Figure 6 FIG. 1 is a schematic diagram of the hardware structure of a clothing recommendation device provided by an embodiment of the present invention. Figure 6 As shown, the clothing recommendation device 60 provided in this embodiment includes: at least one processor 601 and a memory 602. The clothing recommendation device 60 also includes a communication component 603. The processor 601, the memory 602 and the communication component 603 are connected via a bus 604.

[0121] In a specific implementation process, at least one processor 601 executes the computer-executable instructions stored in the memory 602 , so that at least one processor 601 executes the clothing recommendation method executed by the clothing recommendation device 60 as described above.

[0122] When the method of this embodiment is executed by a server, the communication component 603 can send the collected attribute information of the laundry to be washed in the washing machine to the server.

[0123] The specific implementation process of the processor 601 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0124] In the above Figure 6In the illustrated embodiment, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0125] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk storage.

[0126] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0127] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the clothing recommendation method performed by the above clothing recommendation device is implemented.

[0128] The computer-readable storage medium mentioned above can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0129] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0130] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The description and examples are to be considered exemplary only, and the true scope and spirit of the present invention is indicated by the following claims.

[0131] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A clothing recommendation method, characterized in that: include: Obtaining attribute information of at least one piece of clothing to be washed in the washing machine; performing clustering processing on the attribute information of the clothing to determine the attribute information of the clothing corresponding to at least one target user; Pushing clothing information that matches the clothing attribute information corresponding to the target user according to a preset push strategy; The pushing of clothing information matching the clothing attribute information corresponding to the target user according to a preset push strategy includes: Determine the number of different clothes corresponding to the target user among the clothes to be washed in the washing machine within a preset time period; Determining a push time interval for the clothing information of the corresponding target user according to the number of the different clothing items; Pushing clothing information matching the clothing attribute information corresponding to the target user according to the push time interval; After pushing the clothing information matching the clothing attribute information corresponding to the target user according to the preset push strategy, the method further includes: Obtain the clothing information corresponding to the target user who has purchased; Adjusting the clothing attribute information corresponding to the target user according to the clothing information corresponding to the purchased target user; The preset clustering model is optimized according to the adjusted clothing attribute information corresponding to the target user.

2. The method according to claim 1, characterized in that The step of obtaining attribute information of at least one piece of clothing to be washed in the washing machine includes: If a washing machine start signal is detected, a visual sensor is used to collect an image including at least one piece of clothing; Detecting clothing labels in the image to obtain clothing label images; Character recognition is performed on the clothing label image to obtain attribute information of the clothing.

3. The method according to claim 1, characterized in that The step of obtaining attribute information of at least one piece of clothing to be washed in the washing machine includes: If a washing machine start signal is detected, the reader is controlled to read clothing attribute information stored in an electronic tag carried by at least one piece of clothing; The clothing attribute information is obtained from the reader.

4. The method according to any one of claims 1 to 3, characterized in that: The clustering process of the attribute information of the clothing to determine the attribute information of the clothing corresponding to at least one target user includes: Inputting the attribute information of the clothing into a preset clustering model; The attribute information of the clothing is clustered using the preset clustering model, and clothing attribute information corresponding to at least one target user is output.

5. The method according to claim 1, characterized in that After clustering the attribute information of the clothing to determine the attribute information of the clothing corresponding to at least one target user, the method further includes: Pushing washing and care data that matches the clothing attribute information corresponding to the target user.

6. A clothing recommendation device, characterized in that: include: An acquisition module, used for acquiring attribute information of at least one piece of clothing to be washed in the washing machine; a processing module, configured to perform clustering processing on the attribute information of the clothing to determine the attribute information of the clothing corresponding to at least one target user; A push module, used for pushing clothing information matching the clothing attribute information corresponding to the target user according to a preset push strategy; The push module is specifically used to determine the number of different clothes corresponding to the target user among the clothes to be washed in the washing machine within a preset time period; Determining a push time interval for the clothing information of the corresponding target user according to the number of the different clothing items; Pushing clothing information matching the clothing attribute information corresponding to the target user according to the push time interval; An optimization module is used to obtain clothing information corresponding to the target user who has purchased the clothing; Adjusting the clothing attribute information corresponding to the target user according to the clothing information corresponding to the purchased target user; The preset clustering model is optimized according to the adjusted clothing attribute information corresponding to the target user.

7. A clothing recommendation device, characterized in that: include: Memory, processor; Memory; a memory for storing instructions executable by the processor; The processor is configured to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 5 when executed by a processor.

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