CN117172879A - Product recommendation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application provides a product recommendation method, a product recommendation device, electronic equipment and a storage medium. According to the method, basic clothes data corresponding to a target household are obtained, and clothes adding data corresponding to the target household are obtained, wherein the basic clothes data are used for representing self conditions of each piece of clothes, and the clothes adding data are used for representing adding conditions of the clothes; based on the clothing basic data and the clothing adding data, determining family member information and family income information corresponding to the target family; and recommending corresponding target products to the target families based on the family member information and the family income information. Therefore, the conditions of family members and the conditions of family income of the target family can be known through analysis of the conditions of clothes in the target family, so that proper products are recommended to the target family according to the conditions of family members and the conditions of family income, and the sales yield of the products is improved.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a product recommendation method, a device, an electronic device, and a storage medium.
Background
Along with the development of science and technology and the improvement of living standard of people, various products are layered endlessly, and the products comprise: various products of physical type (e.g., food, clothing, various electronic products, etc.), service type products (e.g., laundry services, restaurant services, etc.), and financial type products (e.g., various financial products, etc.), among others. Under the current situation that the types and the quantity of the products are so complicated, how to recommend proper products to users and improve the sales yield of the products become a problem to be solved urgently.
Disclosure of Invention
An embodiment of the application aims to provide a product recommendation method, a device, electronic equipment and a storage medium, so as to solve or partially solve the problems. The specific technical scheme is as follows:
in a first aspect, the present application provides a product recommendation method, including:
acquiring clothing basic data corresponding to a target family, and acquiring clothing adding data corresponding to the target family, wherein the clothing basic data are used for representing self conditions of each piece of clothing, and the clothing adding data are used for representing adding conditions of the clothing;
based on the clothing basic data and the clothing adding data, determining family member information and family income information corresponding to the target family;
and recommending corresponding target products to the target families based on the family member information and the family income information.
In one possible implementation manner, the acquiring the clothing basic data corresponding to the target family includes:
acquiring a current clothes image set corresponding to the target family acquired in a current acquisition period every preset time period, wherein the current clothes image set comprises a plurality of clothes images;
and carrying out image recognition processing on each clothing image to obtain clothing basic data of clothing contained in the clothing image.
In one possible implementation manner, the acquiring the clothing adding data corresponding to the target family includes:
acquiring a reference clothes image set corresponding to the target family collected in a history way, wherein the reference clothes image set contains all clothes images collected in the history way;
determining, for each garment contained in the current garment image set, whether the garment appears in the reference garment image set;
determining that the laundry is a target laundry in a case where the laundry does not appear in the reference laundry image set;
and determining the number of all the target clothes as the clothes increase data.
In one possible implementation manner, the acquiring the current clothing image set corresponding to the target family acquired in the current acquisition period includes:
determining a collection device corresponding to the target family;
and controlling the acquisition device to perform image acquisition operation on the clothes in the preset area to obtain a current clothes image set corresponding to the target family acquired in the current acquisition period.
In one possible embodiment, the laundry base data includes: the price of the clothing, the clothing style and the clothing type;
the determining family member information and family income information corresponding to the target family based on the clothing basic data and the clothing adding data includes:
determining the sex and age of each family member based on the clothes pattern and the clothes type, and taking the sex and age of each family member as the family member information;
the home income information is determined based on the laundry price and the laundry increase data.
In one possible embodiment, after the determining the gender and age of each family member based on the clothing style and the clothing type, the method further comprises:
based on the gender and age of each family member, the relationship between the individual family members is determined, and the relationship between the individual family members is also used as the family member information.
In one possible implementation manner, the recommending the corresponding target product to the target family based on the family member information and the family income information includes:
acquiring a product set, wherein the product set comprises a plurality of products and labels corresponding to the products;
determining a product of which the corresponding label accords with the family member information and the family income information as a target product;
recommending the target product to the target family.
In a second aspect, the present application provides a product recommendation device, comprising:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring clothing basic data corresponding to a target family and clothing addition data corresponding to the target family, wherein the clothing basic data is used for representing the self condition of each piece of clothing, and the clothing addition data is used for representing the addition condition of the clothing;
the determining module is used for determining family member information and family income information corresponding to the target family based on the clothing basic data and the clothing adding data;
and the recommending module is used for recommending the corresponding target product to the target family based on the family member information and the family income information.
In one possible implementation manner, the acquiring module is specifically configured to:
acquiring a current clothes image set corresponding to the target family acquired in a current acquisition period every preset time period, wherein the current clothes image set comprises a plurality of clothes images;
and carrying out image recognition processing on each clothing image to obtain clothing basic data of clothing contained in the clothing image.
In one possible embodiment, the obtaining module is further configured to:
acquiring a reference clothes image set corresponding to the target family collected in a history way, wherein the reference clothes image set contains all clothes images collected in the history way;
determining, for each garment contained in the current garment image set, whether the garment appears in the reference garment image set;
determining that the laundry is a target laundry in a case where the laundry does not appear in the reference laundry image set;
and determining the number of all the target clothes as the clothes increase data.
In one possible embodiment, the obtaining module is further configured to:
determining a collection device corresponding to the target family;
and controlling the acquisition device to perform image acquisition operation on the clothes in the preset area to obtain a current clothes image set corresponding to the target family acquired in the current acquisition period.
In one possible embodiment, the laundry base data includes: the price of the clothing, the clothing style and the clothing type;
the determining module is specifically configured to:
determining the sex and age of each family member based on the clothes pattern and the clothes type, and taking the sex and age of each family member as the family member information;
the home income information is determined based on the laundry price and the laundry increase data.
In one possible embodiment, the determining module is further configured to:
based on the gender and age of each family member, the relationship between the individual family members is determined, and the relationship between the individual family members is also used as the family member information.
In one possible implementation manner, the recommendation module is specifically configured to:
acquiring a product set, wherein the product set comprises a plurality of products and labels corresponding to the products;
determining a product of which the corresponding label accords with the family member information and the family income information as a target product;
recommending the target product to the target family.
In a third aspect, an electronic device is provided, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of the first aspects when executing a program stored on a memory.
In a fourth aspect, a computer-readable storage medium is provided, characterized in that the computer-readable storage medium has stored therein a computer program which, when executed by a processor, implements the method steps of any of the first aspects.
In a fifth aspect, there is provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform any of the product recommendation methods described above.
The embodiment of the application has the beneficial effects that:
the embodiment of the application provides a product recommendation method, a device, electronic equipment and a storage medium, wherein firstly, clothing basic data corresponding to a target family are acquired, clothing adding data corresponding to the target family are acquired, then family member information and family income information corresponding to the target family are determined based on the clothing basic data and the clothing adding data, and finally, corresponding target products are recommended to the target family based on the family member information and the family income information. Therefore, the conditions of family members and the conditions of family income of the target family can be known through analysis of the conditions of clothes in the target family, so that proper products are recommended to the target family according to the conditions of family members and the conditions of family income, and the sales yield of the products is improved.
Of course, it is not necessary for any one product or method of practicing the application to achieve all of the advantages set forth above at the same time.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
One or more embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which the figures of the drawings are not to be taken in a limiting sense, unless otherwise indicated.
FIG. 1 is a flowchart of a product recommendation method according to an embodiment of the present application;
FIG. 2 is a flowchart of another product recommendation method according to an embodiment of the present application;
FIG. 3 is a flowchart of another product recommendation method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a product recommendation device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The following disclosure provides many different embodiments, or examples, for implementing different structures of the application. In order to simplify the present disclosure, components and arrangements of specific examples are described below. They are, of course, merely examples and are not intended to limit the application. Furthermore, the present application may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.
Fig. 1 is a schematic flow chart of a product recommendation method according to an embodiment of the present application. The method can be applied to one or more electronic devices such as smart phones, notebook computers, desktop computers, portable computers, servers and the like. The main execution body of the method may be hardware or software. When the execution body is hardware, the execution body may be one or more of the electronic devices. For example, a single electronic device may perform the method, or a plurality of electronic devices may cooperate with one another to perform the method. When the execution subject is software, the method may be implemented as a plurality of software or software modules, or may be implemented as a single software or software module. The present application is not particularly limited herein.
As shown in fig. 1, the method specifically includes:
s101, acquiring clothing basic data corresponding to a target family, and acquiring clothing adding data corresponding to the target family, wherein the clothing basic data are used for representing self conditions of each piece of clothing, and the clothing adding data are used for representing adding conditions of the clothing.
Clothing base data for characterizing information of each piece of clothing itself, such as clothing style, clothing price, clothing type, etc.
The laundry increase data is used for representing the increase condition of the laundry over a period of time, for example, the laundry increase amount.
As to how to acquire the basic data of the laundry corresponding to the target home and acquire the added data of the laundry corresponding to the target home, detailed explanation will be made by the embodiments described later, and will not be described in detail here.
S102, based on the clothing basic data and the clothing adding data, family member information and family income information corresponding to the target family are determined.
Family member information characterizing which members are included in the target family and personal information of each member.
Household income information used for representing household income situations of target households, such as higher household income, medium household income, lower household income and the like.
In an embodiment of the present application, the laundry base data includes: the specific implementation of the family member information and the family income information corresponding to the target family is determined based on the basic data of the clothes and the added data of the clothes, namely, the clothes price, the clothes style and the clothes type, and comprises the following steps:
and step A1, determining the gender and age of each family member based on the clothes pattern and the clothes type, and taking the gender and age of each family member as the family member information.
For example, the clothes type is a male type, the clothes type is western-style clothes, and the existence of adult men in the target family can be analyzed and obtained; in addition, if the clothes are female, the clothes are jeans, and adult women in the target family can be obtained through analysis; as another example, the clothes are of child type and one-piece dress type, and girls in the target family can be obtained through analysis; for another example, the clothes are old people, the clothes are jackets, and the old people in the target family can be obtained through analysis.
And a step A2 of determining the household income information based on the clothes price and the clothes increase data.
For example, the price of the laundry is generally higher, the data of the laundry increase is higher, the household income of the target household is considered higher, the price of the laundry is generally lower, and the data of the laundry increase is lower, the household income of the target household is considered lower.
In application, the price of the clothes can be known by collecting information on the clothes labels (including price labels, washing labels, brand labels and the like), and particularly, in the case of the price labels, the price of the clothes is directly judged through the price on the price labels, for example, the price is 1000, the price of the clothes is considered to be higher, the price is 80, and the price of the clothes is considered to be lower.
In the case that the price label does not exist on the clothes, the price of the clothes can be judged by the brands marked on the brand labels and/or by washing the clothes marked on the labels, for example, the general price of the clothes of the brand A is higher, the price of the clothes of the brand A is considered to be higher, for example, the general price of the clothes of the silk material is considered to be higher, the price of the clothes of the silk material is considered to be higher, and the like.
In addition, in a further embodiment of the present application, the method may further include the steps of: based on the gender and age of each family member, the relationship between the individual family members is determined, and the relationship between the individual family members is also used as the family member information.
For example, if the target family includes both adult men and adult women, the relationship between the individual members in the target family is considered as a couple.
According to the scheme, intelligent analysis of family member information and family income information can be realized based on the clothing price, style, type and clothing addition data.
In practice, the household member information and the household income information analyzed based on the scheme can be output through the display screen, and a modification button is provided, so that a user can modify the household member information and the household income information according to actual conditions, and the accuracy of the information is improved.
S103, recommending corresponding target products to the target families based on the family member information and the family income information.
Specifically, based on the family member information and the family income information, the implementation of recommending the corresponding target product to the target family may include the following steps:
step B1, obtaining a product set, wherein the product set comprises a plurality of products and labels corresponding to the products;
step B2, determining the products with the corresponding labels conforming to the family member information and the family income information as target products;
and step B3, recommending the target product to the target family.
The label of each product is used for labeling applicable people and product price of the product, for example, the label of infant clothes can be an infant product and a low price, and the label of milk powder suitable for old people can be an old people product and a high price.
Based on the above, in this embodiment, the intelligent recommendation of the product can be realized by matching the target family with the appropriate target product through the family member information and the family income information of the target family and the product label of each product, and recommending the target product.
In the embodiment of the application, firstly, clothing basic data corresponding to a target family are acquired, clothing adding data corresponding to the target family are acquired, then family member information and family income information corresponding to the target family are determined based on the clothing basic data and the clothing adding data, and finally, corresponding target products are recommended to the target family based on the family member information and the family income information. Therefore, the conditions of family members and the conditions of family income of the target family can be known through analysis of the conditions of clothes in the target family, so that proper products are recommended to the target family according to the conditions of family members and the conditions of family income, and the sales yield of the products is improved.
Referring to fig. 2, a flowchart of an embodiment of another product recommendation method is provided in an embodiment of the present application. The flow shown in fig. 2 describes how to acquire the laundry basic data corresponding to the target home based on the flow shown in fig. 1. As shown in fig. 2, the process may include the steps of:
s201, acquiring a current clothes image set corresponding to the target family acquired in a current acquisition period every preset time period, wherein the current clothes image set comprises a plurality of clothes images.
Laundry images, including images containing laundry, as well as images containing laundry labels (e.g., price labels, wash labels, branding labels, etc.).
Specifically, the implementation of obtaining the current clothing image set corresponding to the target family collected in the current collection period may include: determining a collection device corresponding to the target household, and controlling the collection device to conduct image collection operation on clothes in a preset area to obtain a current clothes image set corresponding to the target household, wherein the current clothes image set is collected in a current collection period.
Acquisition device refers to one or more devices, such as cameras, with image acquisition capabilities. The acquisition device can be preset in a preset area and is used for shooting each piece of clothes in the preset area to obtain a clothes image containing the clothes.
A preset area refers to one or more areas of a target home for placing laundry, such as a wardrobe.
In the embodiment, the image acquisition device can acquire images of each piece of clothes in the preset area, so that the automatic acquisition of the current clothes image set is realized.
In practice, in the first acquisition period, the user may take the images of the clothes of each piece of clothes one by using an acquisition device or other photographing devices (such as a smart phone with an image photographing function), so as to obtain an initial clothes image set, and in the subsequent acquisition period, the acquisition device only performs image acquisition on the newly added clothes, for example, performs image acquisition when the user holds the clothes to make an action of putting the clothes into a wardrobe, and adds the newly acquired clothes image to the clothes image set in the previous acquisition period, so as to obtain the current clothes image set. Therefore, the condition that the collected data is incomplete due to the fact that clothes are densely placed can be avoided.
S202, performing image recognition processing on each clothing image to obtain clothing basic data of clothing contained in the clothing image.
In the embodiment of the application, the image containing the clothes is identified by an image identification technology, and the information such as the clothes style, the clothes type and the like is obtained by analysis. The image containing the tag is recognized by a character recognition technique (for example, OCR (Optical Character Recognition, optical character recognition) technique), and information such as a laundry price, laundry material, laundry brand, and the like is analyzed.
Through the flow shown in fig. 2, automatic acquisition of basic data of clothes can be realized based on identification of each clothes image in the current clothes image set corresponding to the target family.
Referring to fig. 3, a flowchart of an embodiment of another product recommendation method is provided in an embodiment of the present application. The flow shown in fig. 3 describes how to acquire the laundry adding data corresponding to the target home based on the flow shown in fig. 2. As shown in fig. 3, the process may include the steps of:
s301, acquiring a reference clothes image set corresponding to the target family collected in a history mode, wherein the reference clothes image set contains all clothes images collected in the history mode.
S302, determining whether the clothes appear in the reference clothes image set for each clothes contained in the current clothes image set.
S303, determining that the clothes are target clothes in the condition that the clothes are not in the reference clothes image set.
S304, determining the quantity of all the target clothes as the clothes increasing data.
S301 to S304 are collectively described below:
in the embodiment of the application, the newly added target clothes in the current acquisition period, namely, the clothes which appear in the current clothes set but do not appear in the reference clothes image set, can be determined as target clothes by comparing the clothes pictures in the current clothes image set with the clothes pictures in the reference clothes image set, and the quantity of the target clothes is determined as clothes adding data.
Thus, the frequency of purchasing clothes of the target family can be known through the clothes adding data, and thus the family income condition of the target family can be known.
In addition, for the case that the acquisition device only acquires images of newly added clothes in a subsequent acquisition period after the initial clothes image set is obtained, whether the clothes image set obtained in the historical acquisition period contains the clothes image of the clothes can be judged for each newly added clothes, and if not, the clothes is considered to be target clothes. Therefore, the data volume of picture comparison can be reduced, and the computing resource is saved.
For example, a higher number of target clothes in the current acquisition cycle means that the frequency of target household clothes purchase is higher during this period, and thus, the household income of the target household is higher by analysis.
Through the flow shown in fig. 3, automatic determination of the laundry augmentation data may be achieved by comparing the laundry image sets acquired in adjacent acquisition cycles.
Based on the same technical concept, the embodiment of the application also provides a product recommendation device, as shown in fig. 4, which comprises:
the acquiring module 401 is configured to acquire basic data of clothes corresponding to a target family, and acquire added data of clothes corresponding to the target family, where the basic data of clothes is used for representing self conditions of each piece of clothes, and the added data of clothes is used for representing added conditions of the clothes;
a determining module 402, configured to determine family member information and family income information corresponding to the target family based on the clothing basic data and the clothing adding data;
and a recommending module 403, configured to recommend a corresponding target product to the target family based on the family member information and the family income information.
In one possible implementation manner, the acquiring module is specifically configured to:
acquiring a current clothes image set corresponding to the target family acquired in a current acquisition period every preset time period, wherein the current clothes image set comprises a plurality of clothes images;
and carrying out image recognition processing on each clothing image to obtain clothing basic data of clothing contained in the clothing image.
In one possible embodiment, the obtaining module is further configured to:
acquiring a reference clothes image set corresponding to the target family collected in a history way, wherein the reference clothes image set contains all clothes images collected in the history way;
determining, for each garment contained in the current garment image set, whether the garment appears in the reference garment image set;
determining that the laundry is a target laundry in a case where the laundry does not appear in the reference laundry image set;
and determining the number of all the target clothes as the clothes increase data.
In one possible embodiment, the obtaining module is further configured to:
determining a collection device corresponding to the target family;
and controlling the acquisition device to perform image acquisition operation on the clothes in the preset area to obtain a current clothes image set corresponding to the target family acquired in the current acquisition period.
In one possible embodiment, the laundry base data includes: the price of the clothing, the clothing style and the clothing type;
the determining module is specifically configured to:
determining the sex and age of each family member based on the clothes pattern and the clothes type, and taking the sex and age of each family member as the family member information;
the home income information is determined based on the laundry price and the laundry increase data.
In one possible embodiment, the determining module is further configured to:
based on the gender and age of each family member, the relationship between the individual family members is determined, and the relationship between the individual family members is also used as the family member information.
In one possible implementation manner, the recommendation module is specifically configured to:
acquiring a product set, wherein the product set comprises a plurality of products and labels corresponding to the products;
determining a product of which the corresponding label accords with the family member information and the family income information as a target product;
recommending the target product to the target family.
In the embodiment of the application, firstly, clothing basic data corresponding to a target family are acquired, clothing adding data corresponding to the target family are acquired, then family member information and family income information corresponding to the target family are determined based on the clothing basic data and the clothing adding data, and finally, corresponding target products are recommended to the target family based on the family member information and the family income information. Therefore, the conditions of family members and the conditions of family income of the target family can be known through analysis of the conditions of clothes in the target family, so that proper products are recommended to the target family according to the conditions of family members and the conditions of family income, and the sales yield of the products is improved.
Based on the same technical concept, the embodiment of the present application further provides an electronic device, as shown in fig. 5, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, where the processor 111, the communication interface 112, and the memory 113 perform communication with each other through the communication bus 114,
a memory 113 for storing a computer program;
the processor 111 is configured to execute a program stored in the memory 113, and implement the following steps:
acquiring clothing basic data corresponding to a target family, and acquiring clothing adding data corresponding to the target family, wherein the clothing basic data are used for representing self conditions of each piece of clothing, and the clothing adding data are used for representing adding conditions of the clothing;
based on the clothing basic data and the clothing adding data, determining family member information and family income information corresponding to the target family;
and recommending corresponding target products to the target families based on the family member information and the family income information.
The communication bus mentioned above for the electronic devices may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The communication interface is used for communication between the electronic device and other devices.
The Memory may include random access Memory (Random Access Memory, RAM) or may include Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processing, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
In yet another embodiment of the present application, there is also provided a computer readable storage medium having stored therein a computer program which when executed by a processor implements the steps of any of the product recommendation methods described above.
In yet another embodiment of the present application, there is also provided a computer program product containing instructions that, when run on a computer, cause the computer to perform any of the product recommendation methods of the above embodiments.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
From the above description of embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus a general purpose hardware platform, or may be implemented by hardware. Based on such understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the related art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the method described in the respective embodiments or some parts of the embodiments.
It is to be understood that the terminology used herein is for the purpose of describing particular example embodiments only, and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises," "comprising," "includes," "including," and "having" are inclusive and therefore specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. The method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order described or illustrated, unless an order of performance is explicitly stated. It should also be appreciated that additional or alternative steps may be used.
The foregoing is only a specific embodiment of the application to enable those skilled in the art to understand or practice the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of product recommendation, the method comprising:
acquiring clothing basic data corresponding to a target family, and acquiring clothing adding data corresponding to the target family, wherein the clothing basic data are used for representing self conditions of each piece of clothing, and the clothing adding data are used for representing adding conditions of the clothing;
based on the clothing basic data and the clothing adding data, determining family member information and family income information corresponding to the target family;
and recommending corresponding target products to the target families based on the family member information and the family income information.
2. The method according to claim 1, wherein the acquiring clothing base data corresponding to the target household includes:
acquiring a current clothes image set corresponding to the target family acquired in a current acquisition period every preset time period, wherein the current clothes image set comprises a plurality of clothes images;
and carrying out image recognition processing on each clothing image to obtain clothing basic data of clothing contained in the clothing image.
3. The method according to claim 2, wherein the acquiring the laundry increase data corresponding to the target home includes:
acquiring a reference clothes image set corresponding to the target family collected in a history way, wherein the reference clothes image set contains all clothes images collected in the history way;
determining, for each garment contained in the current garment image set, whether the garment appears in the reference garment image set;
determining that the laundry is a target laundry in a case where the laundry does not appear in the reference laundry image set;
and determining the number of all the target clothes as the clothes increase data.
4. The method according to claim 2, wherein the acquiring the current clothing image set corresponding to the target household acquired in the current acquisition period includes:
determining a collection device corresponding to the target family;
and controlling the acquisition device to perform image acquisition operation on the clothes in the preset area to obtain a current clothes image set corresponding to the target family acquired in the current acquisition period.
5. The method of claim 1, wherein the clothing base data comprises: the price of the clothing, the clothing style and the clothing type;
the determining family member information and family income information corresponding to the target family based on the clothing basic data and the clothing adding data includes:
determining the sex and age of each family member based on the clothes pattern and the clothes type, and taking the sex and age of each family member as the family member information;
the home income information is determined based on the laundry price and the laundry increase data.
6. The method according to claim 5, wherein after determining the gender and age of each family member based on the clothing style and the clothing type, further comprising:
based on the gender and age of each family member, the relationship between the individual family members is determined, and the relationship between the individual family members is also used as the family member information.
7. The method of claim 1, wherein the recommending the corresponding target product to the target household based on the family member information and the household income information comprises:
acquiring a product set, wherein the product set comprises a plurality of products and labels corresponding to the products;
determining a product of which the corresponding label accords with the family member information and the family income information as a target product;
recommending the target product to the target family.
8. A product recommendation device, the device comprising:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring clothing basic data corresponding to a target family and clothing addition data corresponding to the target family, wherein the clothing basic data is used for representing the self condition of each piece of clothing, and the clothing addition data is used for representing the addition condition of the clothing;
the determining module is used for determining family member information and family income information corresponding to the target family based on the clothing basic data and the clothing adding data;
and the recommending module is used for recommending the corresponding target product to the target family based on the family member information and the family income information.
9. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for carrying out the method steps of any one of claims 1-7 when executing a program stored on a memory.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein a computer program which, when executed by a processor, implements the method steps of any of claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311170044.4A CN117172879A (en) | 2023-09-11 | 2023-09-11 | Product recommendation method and device, electronic equipment and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311170044.4A CN117172879A (en) | 2023-09-11 | 2023-09-11 | Product recommendation method and device, electronic equipment and storage medium |
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| CN117172879A true CN117172879A (en) | 2023-12-05 |
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| CN202311170044.4A Pending CN117172879A (en) | 2023-09-11 | 2023-09-11 | Product recommendation method and device, electronic equipment and storage medium |
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| Country | Link |
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| CN (1) | CN117172879A (en) |
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