CN114219554A - Product distribution method and device based on blind box culture and electronic equipment - Google Patents
Product distribution method and device based on blind box culture and electronic equipment Download PDFInfo
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Abstract
The disclosure relates to a product distribution method and device based on blind box culture, an electronic device and a storage medium. The method comprises the following steps: determining the preliminary type of the blind box according to the preference type information of the user; acquiring user behavior information, and respectively calculating the matching degree of each product with the user behavior information and the preliminary type of the blind box to obtain a matching degree calculation result of the product; sorting the products in a descending order according to the matching degree calculation result, and combining the products with the matching degree ranking reaching a preset threshold value after the descending order into a set of blind box products; and after a purchase instruction sent by the user equipment is received, randomly displaying one product in the set of blind box products on a blind box distribution page as a blind box product distributed to the user. By adopting the method, the purchasing demand of the user can be met, the hunting psychology of the user can be met, and the interestingness is increased.
Description
Technical Field
The disclosure relates to the technical field of big data analysis, in particular to a product distribution method and device based on blind box culture and electronic equipment.
Background
With the development of product sale technology, a product online recommendation scheme appears, and a consumer can buy products through an online channel conveniently and efficiently by the scheme.
In the related technology, the existing online product recommendation method is specifically based on product recommendation of customer behaviors, mainly by continuously collecting behaviors of clicking and staying of customers, product contents which are interesting to the customers are obtained through calculation, the product contents obtained through calculation are recommended to the customers, and the probability of purchasing products by the customers is improved.
Disclosure of Invention
The invention provides a product distribution method based on blind box culture, which can provide a group of better product recommendation for a user, simultaneously meet the hunting psychology of the user and meet the requirements of the user. The technical scheme of the disclosure includes the following:
according to a first aspect of the embodiments of the present disclosure, there is provided a product distribution method based on a blind box culture, including:
determining the preliminary type of the blind box according to the preference type information of the user;
acquiring user behavior information, and respectively calculating the matching degree of each product and the user behavior information and the matching degree of each product and the preliminary type of the blind box to obtain the calculation result of the matching degree of the product, wherein the user behavior information comprises the acquired operation data executed by the user on a product display page;
sorting the products in a descending order according to the matching degree calculation result, and combining the products with the matching degree ranking reaching a preset threshold value after the descending order into a set of blind box products;
after a purchase instruction sent by user equipment is received, a random number used for selecting products is obtained from a server based on the purchase instruction, and one product corresponding to the random number in the set of blind box products is displayed on a blind box distribution page and serves as the blind box product distributed to a user.
In one embodiment, after receiving a purchase instruction sent by a user device, the method for displaying a product corresponding to a random number in the set of blind box products on a blind box distribution page includes:
determining a unique identification for each product contained in the set of blind box products;
after receiving the purchase instruction, acquiring a random number generated by a cloud logic computing center;
determining a target identification mark corresponding to the random number in the unique identification mark;
and displaying the product corresponding to the target identification mark on the blind box distribution page as a blind box product distributed to the user according to the target identification mark.
In one embodiment, before displaying the item of the set of blind box products corresponding to the random number on the blind box distribution page, the method further includes:
displaying all the blind box products and product introduction and risk notification information corresponding to the blind box products on the blind box distribution page.
In one embodiment, the user preference type is determined based on a product type determined by a user when the user browses the blind box distribution page, the product displayed on the blind box distribution page is determined according to a user information analysis result, and the user information analysis result comprises a predicted product type liked by the user and a predicted price interval that the user can bear.
In one embodiment, the user information analysis result is obtained by calculating user information, and the user information at least comprises one of user purchase records, product contents browsed for multiple times and purchasing power information.
In one embodiment, the method further comprises the following steps:
displaying the user information analysis result on the blind box distribution page;
modifying and/or confirming the user information analysis result on the blind box allocation page based on the received user instruction.
According to a second aspect of the embodiments of the present disclosure, there is provided a product dispensing device based on a blind box culture, comprising:
the type determining module is used for determining the blind box preliminary type according to the user preference type;
the matching degree calculation module is used for acquiring user behavior information, calculating the matching degree of each product and the user behavior information and the matching degree of each product and the preliminary type of the blind box respectively, and obtaining the calculation result of the matching degree of the product, wherein the user behavior information comprises the acquired operation data executed by the user on a product display page;
the product determining module is used for ranking the products according to the matching degree according to the calculation result and combining the products with the matching degree ranking reaching a preset threshold value into a set of blind box products;
and the product output module is used for acquiring a random number for selecting a product from the server based on the purchase instruction after receiving the purchase instruction sent by the user equipment, and displaying a product corresponding to the random number in the set of blind box products on a blind box distribution page to serve as the blind box product distributed to the user.
In one embodiment, the product output module is further configured to:
determining a unique identification for each product contained in the set of blind box products;
after receiving the purchase instruction, acquiring a random number generated by a cloud logic computing center;
determining a target identification mark corresponding to the random number in the unique identification mark;
and displaying the product corresponding to the target identification mark on the blind box distribution page as a blind box product distributed to the user according to the target identification mark.
In one embodiment, the product determination module is further configured to:
displaying all the blind box products and product introduction and risk notification information corresponding to the blind box products on the blind box distribution page.
In one embodiment, the type determining module is further configured to: and determining the user preference type based on the product type determined when the user browses the blind box distribution page, wherein the product displayed on the blind box distribution page is determined according to a user information analysis result, and the user information analysis result comprises a predicted product type liked by the user and a predicted price interval which can be born by the user.
In one embodiment, the type determining module is further configured to calculate user information to obtain the user information analysis result, where the user information includes at least one of a user purchase record, product content viewed multiple times, and purchasing power information.
In one embodiment, the product determination module is further configured to:
displaying the user information analysis result on the blind box distribution page;
modifying and/or confirming the user information analysis result on the blind box allocation page based on the received user instruction.
According to a third aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of blind box culture based product distribution of any of the above embodiments.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium, wherein instructions, when executed by a processor of an electronic device, enable the electronic device to perform the method of blind box culture based product distribution according to any one of the above embodiments.
According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product comprising instructions, wherein the instructions, when executed by a processor of an electronic device, enable the electronic device to perform the method for product allocation based on blind box culture of any one of the above embodiments.
According to the product distribution method, the product distribution device, the computer equipment, the storage medium and the computer program product based on the blind box culture, the product is recommended according to the preference type of the user, and the purpose of recommending the product meeting the purchase intention to the user can be achieved. Meanwhile, through introducing the blind box culture into the product sale, the matching degree calculation is carried out on the product and the user behavior information, the product and the blind box preliminary type, the product with the matching degree ranking reaching the preset threshold value is combined into a set of blind box products, the products contained in the set of blind box products are randomly distributed, and the randomly distributed products are used as the products purchased by the user, so that the aims of meeting the purchase demand of the user, meeting the hunting psychology of the user, increasing the interesting beneficial effect, increasing the product sales volume, expanding the application space of the blind box and enriching the blind box related technology can be achieved in product recommendation.
In the embodiments of the present disclosure, it is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.
Fig. 1 is a diagram illustrating an application environment for a blind box culture based product distribution method according to an exemplary embodiment.
FIG. 2 is a flow diagram illustrating a method for blind box culture based product distribution according to an exemplary embodiment.
FIG. 3 is a flow diagram illustrating a method for blind box culture based product distribution according to another exemplary embodiment.
FIG. 4 is a block diagram illustrating a blind box culture based product dispensing device according to an exemplary embodiment.
FIG. 5 is a block diagram illustrating an electronic device in accordance with an example embodiment.
Detailed Description
In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
It should also be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for presentation, analyzed data, etc.) referred to in the present disclosure are both information and data that are authorized by the user or sufficiently authorized by various parties.
The product distribution method based on the blind box culture provided by the disclosure can be applied to the application environment as shown in fig. 1. Wherein the terminal 102 interacts with the server 104 over a network. The server 104 determines a blind box preliminary type based on the user preference type information. The terminal 102 collects user behavior information and sends the user behavior information to the server 104, and the server 104 respectively calculates the matching degree of each product with the user behavior information and the blind box preliminary type to obtain the product matching degree calculation result. And the server 104 performs descending sorting on the products according to the matching degree calculation result, and combines the products with the matching degree ranking reaching a preset threshold value after the descending sorting into a set of blind box products. After the terminal 102 sends a purchase instruction of the user equipment to the server 104, the server 104 randomly displays one product in the set of blind box products on the blind box distribution page as a blind box product distributed to the user. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
Fig. 2 is a flow chart illustrating a method for blind box culture based product distribution as shown in fig. 2 for use in the application environment shown in fig. 1, according to an exemplary embodiment, including the following steps.
And S202, determining the blind box preliminary type according to the user preference type information.
Wherein, the user preference type may refer to a product type preferred by the user. The product may be a financial product, a service product, a virtual resource product, or other product. A blind box is a toy box where the consumer cannot know the specific product style in advance. The blind box preliminary type refers to a preliminarily determined type of product loaded into the blind box.
Specifically, the product type preferred by the user is determined as the blind box preliminary type. The products may include financial products, service products, virtual resource products, and the like. The financial product may refer to various carriers used by funds in the financing process and may also be referred to as a financial instrument. The product may be a currency, gold, foreign exchange, stock, futures, options, fund, policy, or the like in a financial product. The service product can be experience ticket, entrance ticket and other products, and can also be a product service provided for customers. The virtual resource product may be a game piece, a game equipment, a game skin, or the like. The product types can be divided into more detailed types according to actual needs, for example, money products can be divided into short-term bonds, large-amount transferable deposit slips, commercial bills, bank acceptance remittance bills, buyback agreements, dollars and the like. The blind box can be a physical box or a virtual box.
S204, collecting user behavior information, respectively calculating the matching degree of each product and the user behavior information and the matching degree of each product and the preliminary type of the blind box, and obtaining the calculation result of the matching degree of the products, wherein the user behavior information comprises the acquired operation data executed by the user on a product display page.
Specifically, user behavior information is collected from a terminal, the user behavior information includes acquired operation data executed by a user on a product display page, and the user behavior information may include information such as click behavior and stay time. And comprehensively considering the user behavior information and the blind box preliminary type, respectively calculating the matching degree of each product and the user behavior information, and then respectively calculating the matching degree of each product and the blind box preliminary type to obtain the matching degree calculation result of the product. For example, when the user preference type is stocks, stock products can obtain higher matching degree in the matching degree calculation; when the user behavior information comprises the behavior that the user clicks more stock products and fund products, the stock products and the fund products can obtain higher matching degree in the matching degree calculation; when the user behavior information comprises that the user stays on the page of the gold product for a long time, the gold product obtains a high matching degree in the calculation of the matching degree. It should be noted that, the specific calculation manner is determined according to actual needs, and the factors to be considered may be weighted in the matching degree calculation, for example, a higher weight may be given to a user preference type, and different weights may be given to different user behavior information.
And S206, sorting the products in a descending order according to the matching degree calculation result, and combining the products with the matching degree ranking reaching a preset threshold value after the descending order into a set of blind box products.
Specifically, the products are sorted in a descending order according to the matching degree calculation result, and the higher the matching degree is, the higher the ranking is. The preset threshold may be set according to actual needs, for example, the preset threshold may be set to 10 top-ranked matching degrees. And combining the products with the descending matching degree ranking reaching a preset threshold value into a set of blind box products, wherein the set of blind box products can contain multiple types of products.
And S208, after a purchase instruction sent by user equipment is received, acquiring a random number for selecting a product from a server based on the purchase instruction, and displaying a product corresponding to the random number in the set of blind box products on a blind box distribution page to serve as a blind box product distributed to a user.
The blind box distribution page refers to a page capable of showing products to a user and can also be used for showing other contents to be shown to the user.
Specifically, after a purchase instruction sent by user equipment is received, a random number for selecting a product is obtained from a server based on the purchase instruction, and a product corresponding to the random number in the set of blind box products is displayed on a blind box distribution page to serve as a blind box product distributed to a user. And when the purchase instruction is to purchase two or more blind box products, correspondingly and randomly displaying the two or more blind box products in the set of blind box products on the blind box distribution page as the blind box products distributed to the user according to the purchase instruction.
In this embodiment, by recommending a product according to the purchase intention of the user, the purpose of recommending a product satisfying the purchase intention to the user can be achieved. Meanwhile, by introducing the blind box culture into the sale of products, the products with the matching degree ranking reaching the preset threshold value are combined into a set of blind box products, the products contained in the set of blind box products are randomly distributed, and the randomly distributed products are used as the products purchased by the user, so that the purchasing intention of the user can be met and the hunting psychology of the user can be met when the products are recommended on a product line.
In an exemplary embodiment, as shown in fig. 3, after receiving a purchase instruction sent by a user equipment, acquiring a random number for selecting a product from a server based on the purchase instruction, and displaying a product corresponding to the random number in the set of blind box products on a blind box distribution page as a blind box product distributed to a user includes:
s302, determining the unique identification of each product contained in the set of blind box products.
S304, after receiving the purchase instruction, acquiring a random number generated by the cloud logic computing center.
S306, determining a target identification mark corresponding to the random number in the unique identification mark.
And S308, displaying the product corresponding to the target identification mark on the blind box distribution page as the blind box product distributed to the user according to the target identification mark.
Specifically, each product contained in the set of blind box products is provided with a unique identification mark. The unique identification mark may correspond to a random number one by one, or the random number may correspond to a unique one of the unique identification marks through a preset mapping relationship. After a purchase instruction sent by the user equipment is received, a random number generated by the cloud logic computing center is used. And determining a corresponding unique identification mark according to the random number generated by the cloud logic computing center, wherein the corresponding unique identification mark is the target identification mark. And displaying the product corresponding to the target identification mark on the blind box distribution page as a blind box product distributed to the user according to the target identification mark. The random number may be generated by a randomization algorithm (randomized algorithm), where a random function is used, and a return value of the random function directly or indirectly affects an execution flow or an execution result of the algorithm. The randomization algorithm may be a Monte Carlo algorithm, a Las Vegas algorithm.
In the embodiment, an implementation scheme for randomly selecting a product from a set of blind box products is provided, a random number is generated by means of the cloud logic technology center, and the randomly distributed product is determined by the random number, so that the speed is high, the uniqueness is guaranteed, the randomness is higher, and the purpose of meeting the hunting psychology of a user is favorably achieved.
In an exemplary embodiment, before the randomly displaying the product in the set of blind box products corresponding to the random number on the blind box distribution page, the method further includes: displaying all the blind box products and product introduction and risk notification information corresponding to the blind box products on the blind box distribution page.
Specifically, all the blind box products and product introduction and risk notification information corresponding to the blind box products are displayed on the blind box distribution page. The product introduction includes packaging instructions for the respective product. The risk informing information comprises a matching degree calculation result prompting the blind box product, and the risk informing information also comprises a step of ensuring the user to confirm whether to purchase the blind box product.
In the embodiment, all the blind box products, and the product introduction and risk notification information corresponding to the blind box products are displayed on the blind box distribution page, so that the user can know all the possibilities of the blind box products distributed by the user, and the aim of better meeting the purchase demands of the user when the products are recommended is favorably fulfilled. Meanwhile, the step increases the interest of the user when purchasing the product and is beneficial to achieving the purpose of meeting the hunt psychology of the user.
In an exemplary embodiment, the user preference type is determined based on a product type determined by a user when browsing the blind box distribution page, and the product displayed on the blind box distribution page is determined according to a user information analysis result, wherein the user information analysis result comprises a predicted product type liked by the user and a predicted price interval that the user can bear.
Specifically, the products displayed on the blind box distribution page are determined according to the user information analysis result. The user information analysis result comprises a predicted product type liked by the user and a predicted price interval that the user can bear. After browsing the products on the blind box distribution page, the user selects the preference type of the user. When the user information analysis result cannot be obtained, displaying hot products on the blind box distribution page, and at the moment, the user can still select the preference type of the user after browsing the blind box distribution page.
In the embodiment, the products are displayed on the blind box distribution page according to the user analysis result, so that the user can determine the preference type after browsing the blind box distribution page, and the purpose of better meeting the purchase demand of the user during product recommendation is favorably achieved.
In an exemplary embodiment, the user information analysis result is obtained by calculating user information, and the user information at least includes one of a user purchase record, product content viewed multiple times, and purchasing power information.
Specifically, the user information is calculated to obtain the user information analysis result, and the specific calculation method is not limited. The user information at least comprises one of a user purchase record, product contents browsed for multiple times and purchasing power information. The user information can be obtained by inquiring a cloud database and the like. The purchasing power information may be predicted purchasing power information.
In the embodiment, the user information analysis result is obtained by calculating the user information such as the user purchase record, the product content browsed for many times, the purchasing power information and the like, so that the aim of better meeting the user purchase demand during product recommendation is favorably fulfilled.
In an exemplary embodiment, the method for product distribution based on the blind box culture further comprises: displaying the user information analysis result on the blind box distribution page; modifying and/or confirming the user information analysis result on the blind box allocation page based on the received user instruction.
Specifically, the user information analysis result is displayed on the blind box distribution page, and after browsing the user information analysis result, the user instruction is sent through user equipment, and the user instruction is used for modifying and/or confirming the user information analysis result on the blind box distribution page.
In the embodiment, the user information analysis result is displayed on the blind box distribution page for the user to modify and confirm, so that a more accurate user information analysis result can be obtained, and the aim of better meeting the purchase demand of the user during product recommendation can be fulfilled.
It should be understood that although the steps in the flowcharts of fig. 2 and 3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2 and 3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
It is understood that the same/similar parts between the embodiments of the method described above in this specification can be referred to each other, and each embodiment focuses on the differences from the other embodiments, and it is sufficient that the relevant points are referred to the descriptions of the other method embodiments.
FIG. 4 is a block diagram illustrating a blind box culture based product dispensing device according to an exemplary embodiment. Referring to fig. 4, the apparatus includes a type determining module 402, a matching degree calculating module 404, a product determining module 406, and a product output module 408, wherein:
a type determining module 402, configured to determine a blind box preliminary type according to the user preference type.
The matching degree calculation module 404 is configured to collect user behavior information, calculate matching degrees of each product and the user behavior information, and match degrees of each product and the preliminary type of the blind box respectively, and obtain a matching degree calculation result of the product, where the user behavior information includes acquired operation data executed by a user on a product display page.
And the product determining module 406 is configured to rank the products according to the matching degrees according to the calculation result, and combine the products with the matching degrees reaching a preset threshold value into a set of blind box products.
The product output module 408 is configured to, after receiving a purchase instruction sent by the user equipment, obtain a random number for selecting a product from the server based on the purchase instruction, and display a product corresponding to the random number in the set of blind box products on a blind box distribution page as a blind box product distributed to the user.
In an exemplary embodiment, the product output module 408 is further configured to: determining a unique identification for each product contained in the set of blind box products; after receiving the purchase instruction, acquiring a random number generated by a cloud logic computing center; determining a target identification mark corresponding to the random number in the unique identification mark; and displaying the product corresponding to the target identification mark on a blind box distribution page as a blind box product distributed to a user according to the target identification mark.
In an exemplary embodiment, the product determination module 406 is further configured to: displaying all the blind box products and product introduction and risk notification information corresponding to the blind box products on the blind box distribution page.
In an exemplary embodiment, the type determining module 402 is further configured to: and determining a user preference type based on the product type determined when the user browses the blind box distribution page, wherein the product displayed on the blind box distribution page is determined according to a user information analysis result, and the user information analysis result comprises a predicted product type liked by the user and a predicted price interval which can be born by the user.
In an exemplary embodiment, the type determining module 402 is further configured to: and calculating user information to obtain a user information analysis result, wherein the user information at least comprises one of user purchase records, product contents browsed for multiple times and purchasing power information.
In an exemplary embodiment, the product determination module 406 is further configured to:
displaying the analysis result on the blind box distribution page;
modifying and/or confirming the analysis result on the blind box assignment page based on the received user instruction.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
FIG. 5 is a block diagram illustrating an electronic device Z00 for product distribution based on the blind box culture, according to an example embodiment. For example, electronic device Z00 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and so forth.
Referring to fig. 5, electronic device Z00 may include one or more of the following components: a processing component Z02, a memory Z04, a power component Z06, a multimedia component Z08, an audio component Z10, an interface for input/output (I/O) Z12, a sensor component Z14 and a communication component Z16.
The processing component Z02 generally controls the overall operation of the electronic device Z00, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component Z02 may include one or more processors Z20 to execute instructions to perform all or part of the steps of the method described above. Further, the processing component Z02 may include one or more modules that facilitate interaction between the processing component Z02 and other components. For example, the processing component Z02 may include a multimedia module to facilitate interaction between the multimedia component Z08 and the processing component Z02.
The memory Z04 is configured to store various types of data to support operations at the electronic device Z00. Examples of such data include instructions for any application or method operating on electronic device Z00, contact data, phonebook data, messages, pictures, videos, and the like. The memory Z04 may be implemented by any type or combination of volatile or non-volatile storage devices, 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, optical disk, or graphene memory.
The power supply component Z06 provides power to the various components of the electronic device Z00. The power component Z06 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device Z00.
The multimedia component Z08 comprises a screen providing an output interface between the electronic device Z00 and the user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component Z08 includes a front facing camera and/or a rear facing camera. When the electronic device Z00 is in an operating mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component Z10 is configured to output and/or input an audio signal. For example, the audio component Z10 includes a Microphone (MIC) configured to receive external audio signals when the electronic device Z00 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory Z04 or transmitted via the communication component Z16. In some embodiments, the audio component Z10 also includes a speaker for outputting audio signals.
The I/O interface Z12 provides an interface between the processing component Z02 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly Z14 includes one or more sensors for providing status assessment of various aspects to the electronic device Z00. For example, the sensor assembly Z14 may detect the open/closed state of the electronic device Z00, the relative positioning of the components, such as the display and keypad of the electronic device Z00, the sensor assembly Z14 may also detect a change in the position of the electronic device Z00 or electronic device Z00 components, the presence or absence of user contact with the electronic device Z00, the orientation or acceleration/deceleration of the device Z00, and a change in the temperature of the electronic device Z00. The sensor assembly Z14 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly Z14 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly Z14 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component Z16 is configured to facilitate wired or wireless communication between the electronic device Z00 and other devices. The electronic device Z00 may have access to a wireless network based on a communication standard, such as WiFi, a carrier network (such as 2G, 3G, 4G, or 5G), or a combination thereof. In an exemplary embodiment, the communication component Z16 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component Z16 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device Z00 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic components for performing the above-described methods.
In an exemplary embodiment, a computer readable storage medium is also provided, for example the memory Z04, comprising instructions executable by the processor Z20 of the electronic device Z00 to perform the above method. For example, the computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
In an exemplary embodiment, a computer program product is also provided, which comprises instructions executable by the processor Z20 of the electronic device Z00 to perform the above method.
It should be noted that the descriptions of the above-mentioned apparatus, the electronic device, the computer-readable storage medium, the computer program product, and the like according to the method embodiments may also include other embodiments, and specific implementations may refer to the descriptions of the related method embodiments, which are not described in detail herein.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements 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 disclosure is limited only by the appended claims.
Claims (15)
1. A method for product distribution based on a blind box culture, comprising:
determining the preliminary type of the blind box according to the preference type information of the user;
acquiring user behavior information, and respectively calculating the matching degree of each product and the user behavior information and the matching degree of each product and the preliminary type of the blind box to obtain the calculation result of the matching degree of the product, wherein the user behavior information comprises the acquired operation data executed by the user on a product display page;
sorting the products in a descending order according to the matching degree calculation result, and combining the products with the matching degree ranking reaching a preset threshold value after the descending order into a set of blind box products;
after a purchase instruction sent by user equipment is received, a random number used for selecting products is obtained from a server based on the purchase instruction, and one product corresponding to the random number in the set of blind box products is displayed on a blind box distribution page and serves as the blind box product distributed to a user.
2. The blind box culture based product distribution method according to claim 1, wherein the step of obtaining a random number for selecting a product from a server based on a purchase instruction after receiving the purchase instruction from the user equipment, and displaying a product corresponding to the random number in the set of blind box products on a blind box distribution page as the blind box product distributed to the user comprises:
determining a unique identification for each product contained in the set of blind box products;
after receiving the purchase instruction, acquiring a random number generated by a cloud logic computing center;
determining a target identification mark corresponding to the random number in the unique identification mark;
and displaying the product corresponding to the target identification mark on the blind box distribution page as a blind box product distributed to the user according to the target identification mark.
3. The blind box culture based product distribution method of claim 1, further comprising, before the displaying one of the set of blind box products corresponding to the random number on a blind box distribution page:
displaying all the blind box products and product introduction and risk notification information corresponding to the blind box products on the blind box distribution page.
4. The blind box culture based product allocation method according to claim 1, wherein the user preference type is determined based on a product type determined by a user when browsing the blind box allocation page, products displayed on the blind box allocation page are determined according to a user information analysis result, and the user information analysis result comprises a predicted product type preferred by the user and a predicted price interval that the user can bear.
5. The blind box culture based product distribution method according to claim 4, wherein the user information analysis result is obtained by calculating user information, and the user information at least comprises one of user purchase record, product content viewed multiple times, and purchasing power information.
6. The blind box culture based product distribution method of claim 4, further comprising:
displaying the user information analysis result on the blind box distribution page;
modifying and/or confirming the user information analysis result on the blind box allocation page based on the received user instruction.
7. A blind-box culture based product dispensing device, comprising:
the type determining module is used for determining the blind box preliminary type according to the user preference type;
the matching degree calculation module is used for acquiring user behavior information, calculating the matching degree of each product and the user behavior information and the matching degree of each product and the preliminary type of the blind box respectively, and obtaining the calculation result of the matching degree of the product, wherein the user behavior information comprises the acquired operation data executed by the user on a product display page;
the product determining module is used for ranking the products according to the matching degree according to the calculation result and combining the products with the matching degree ranking reaching a preset threshold value into a set of blind box products;
and the product output module is used for acquiring a random number for selecting a product from the server based on the purchase instruction after receiving the purchase instruction sent by the user equipment, and displaying a product corresponding to the random number in the set of blind box products on a blind box distribution page to serve as the blind box product distributed to the user.
8. The blind box culture based product dispensing device of claim 7, wherein the product output module is further configured to:
determining a unique identification for each product contained in the set of blind box products;
after receiving the purchase instruction, acquiring a random number generated by a cloud logic computing center;
determining a target identification mark corresponding to the random number in the unique identification mark;
and displaying the product corresponding to the target identification mark on the blind box distribution page as a blind box product distributed to the user according to the target identification mark.
9. The blind box culture based product dispensing device of claim 7, wherein the product determination module is further configured to:
displaying all the blind box products and product introduction and risk notification information corresponding to the blind box products on the blind box distribution page.
10. The blind box culture based product dispensing device of claim 7, wherein the type determination module is further configured to:
determining the user preference type based on the product type determined by the user when browsing the blind box distribution page; and determining products displayed on the blind box distribution page according to a user information analysis result, wherein the user information analysis result comprises a predicted product type liked by the user and a predicted price interval which can be borne by the user.
11. The blind box culture based product dispensing device of claim 10, wherein the type determination module is further configured to:
and calculating user information to obtain a user information analysis result, wherein the user information at least comprises one of user purchase records, product contents browsed for multiple times and purchasing power information.
12. The blind box culture based product dispensing device of claim 10, wherein the product determination module is further configured to:
and displaying the user information analysis result on the blind box distribution page, and modifying and/or confirming the user information analysis result on the blind box distribution page based on the received user instruction.
13. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the blind box culture based product distribution method of any one of claims 1 to 6.
14. A computer-readable storage medium, wherein instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the blind box culture based product distribution method of any one of claims 1 to 6.
15. A computer program product comprising instructions therein, wherein the instructions, when executed by a processor of an electronic device, enable the electronic device to perform the method of blind box culture based product distribution according to any one of claims 1 to 6.
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