Precise pushing method and system based on e-commerce platform
By acquiring users' browsing history and latest product information from e-commerce platforms, relevant product information is generated to achieve accurate recommendations, solving the problem of low relevance in e-commerce platform recommendations and improving the accuracy of recommendations.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FOSHAN POLYTECHNIC
- Filing Date
- 2026-01-23
- Publication Date
- 2026-05-15
AI Technical Summary
E-commerce platforms often lack in-depth understanding of users' potential interests and needs during product recommendations, resulting in low relevance of recommendations.
By acquiring the latest and historical product browsing information of target users, related product information is generated, and target product information is generated based on this information. Finally, product push instructions are generated to achieve accurate recommendations.
It achieves accurate capture of target users' interests, preferences, and behavioral characteristics, thereby improving the relevance of product recommendations.
Smart Images
Figure CN122048475A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of internet data analysis, and more specifically, to a method and system for precise push notifications based on e-commerce platforms. Background Technology
[0002] E-commerce platforms not only bridge the gap between merchants and consumers, enabling convenient and quick online transactions of goods and services, but also reduce the rent and labor costs of traditional brick-and-mortar stores by displaying product information online.
[0003] Currently, e-commerce platforms often rely on users' historical browsing data to repeatedly push products during the product recommendation process. This lacks in-depth analysis of users' potential interests and needs, making it difficult to accurately predict new products that users might be interested in. As a result, the recommendation relevance is low and needs further improvement. Summary of the Invention
[0004] Based on this, embodiments of this application provide a precise push method and system based on an e-commerce platform to solve the problem of low recommendation relevance in the prior art.
[0005] In a first aspect, embodiments of this application provide a method for precise push notifications based on an e-commerce platform, the method comprising: Based on a preset e-commerce platform and according to a preset sampling time period, information on the latest browsed products and multiple historical browsed products of the target user is obtained. Based on the most recently viewed product, generate information on multiple associated products corresponding to the most recently viewed product; Based on multiple related product information and multiple historically browsed product information, target product information is generated; Based on the target product information, a product push instruction is generated.
[0006] Compared with existing technologies, the beneficial effects are as follows: The precise push method based on e-commerce platforms provided in this application allows the terminal device to first quickly obtain the latest browsed products and multiple historically browsed product information of the target user based on the e-commerce platform and the sampling time period. Then, based on the latest browsed products, it accurately generates multiple related product information corresponding to the latest browsed products. Based on the multiple related product information and multiple historically browsed product information, it effectively generates target product information. Finally, based on the target product information, it efficiently generates product push instructions, thereby accurately capturing the target user's interests, preferences, and behavioral characteristics, and accurately recommending new products of interest to the target user, which to a certain extent solves the problem of low recommendation relevance in the current system.
[0007] Secondly, embodiments of this application provide a precise push system based on an e-commerce platform, the system comprising: The latest viewed products acquisition module is used to acquire the latest viewed products and multiple historical viewed products information of target users based on a preset e-commerce platform and a preset sampling time period. Related product information generation module: used to generate multiple related product information corresponding to the latest viewed product based on the latest viewed product; Target product information generation module: used to generate target product information based on multiple related product information and multiple historically browsed product information; Product push instruction generation module: used to generate product push instructions based on the target product information.
[0008] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.
[0009] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.
[0010] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description
[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.
[0012] Figure 1 This is a flowchart illustrating a precise push method provided in an embodiment of this application; Figure 2 This is a flowchart illustrating step S200 in a precise push method provided in an embodiment of this application; Figure 3 This is a flowchart illustrating step S300 in a precise push method provided in an embodiment of this application; Figure 4 This is a flowchart illustrating the process after step S320 in a precise push method provided in an embodiment of this application; Figure 5 This is a flowchart illustrating the process after step S350 in a precise push method provided in an embodiment of this application; Figure 6 This is a block diagram of a precision push system provided in an embodiment of this application; Figure 7 This is a schematic diagram of a terminal device provided in an embodiment of this application. Detailed Implementation
[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0014] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0015] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0016] To illustrate the technical solution described in this application, specific embodiments are provided below.
[0017] Please see Figure 1 , Figure 1 This is a flowchart illustrating the precise push method based on an e-commerce platform provided in this embodiment. In this embodiment, the executing entity of the precise push method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, mobile phones, tablets, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This embodiment does not impose any restrictions on the specific type of terminal device.
[0018] Please see Figure 1 The precise push method provided in this application includes, but is not limited to, the following steps: In S100, based on a preset e-commerce platform and according to a preset sampling time period, information on the target user's latest browsed products and multiple historically browsed products is obtained.
[0019] Specifically, the terminal device can first obtain the latest browsed products and multiple historical browsed products of the target user based on a preset e-commerce platform and a preset sampling time period. The specific value of the sampling time period can be customized. The latest browsed products are used to describe the products recently browsed by the target user, and the historical browsed products information is used to describe the products browsed by the target user during the sampling time period other than the latest browsed products.
[0020] In S200, based on the most recently viewed product, multiple related product information corresponding to the most recently viewed product are generated.
[0021] Specifically, after the terminal device obtains the information of the latest browsed products and the products browsed in the past, the terminal device can quickly generate multiple related product information corresponding to the latest browsed products. Among them, the related product information is used to describe the products associated with the latest browsed products. For example, when the latest browsed product is a mobile phone, the related product information can be a mobile phone screen protector.
[0022] In some possible implementations, for quickly generating associated product information, please refer to [link to relevant documentation]. Figure 2 Step S200 includes, but is not limited to, the following steps: In S210, obtain the first product category information of the latest browsed product.
[0023] Specifically, the terminal device can first obtain the first product category information of the most recently viewed product, where the first product category information is used to describe the product category of the most recently viewed product.
[0024] In S220, based on a preset associated product database, multiple associated product information corresponding to the most recently viewed product is determined according to the first product category information.
[0025] Without loss of generality, the associated product database pre-stores multiple candidate category information, related category information corresponding to each candidate category information, and multiple related product information corresponding to each related category information; the associated product information is used to describe the related product information corresponding to the related category information that is the same as the first product category information. Specifically, after the terminal device obtains the first product category information, the terminal device can determine the related category information that is the same as the first product category information based on the preset associated product database, and then further determine multiple related product information corresponding to the related category information, and determine all of the multiple related product information as associated product information.
[0026] In S300, target product information is generated based on multiple related product information and multiple historical browsing product information.
[0027] Specifically, after the terminal device generates associated product information, it can accurately generate target product information based on multiple associated product information and multiple historical browsing product information. The target product information is used to describe new products that the target user is interested in.
[0028] In S400, a product push instruction is generated based on the target product information.
[0029] Specifically, after the terminal device generates target product information, it can effectively generate product push instructions based on the target product information. These product push instructions are used to instruct the target product information to be accurately pushed to the target user.
[0030] In some possible implementations, in order to facilitate the accurate generation of target product information, the method may include, but is not limited to, the following steps before step S300: In S301, the second product category information of the historically viewed product information is obtained, and the third product category information of the associated product information is obtained.
[0031] Specifically, the terminal device can obtain second product category information of historically browsed product information and third product category information of associated product information. The second product category information is used to describe the product category of the historically browsed product information, and the third product category information is used to describe the product category of the associated product information.
[0032] Accordingly, please refer to Figure 3 Step S300 includes, but is not limited to, the following steps: In S310, for each associated product information: based on the associated product information, generate overlapping quantity information.
[0033] Without loss of generality, overlapping quantity information is used to describe the quantity corresponding to the second product category information that is the same as the third product category information.
[0034] Specifically, after the terminal device obtains the second product category information and the third product category information, the terminal device can perform the following process for each associated product category information: first, determine the second product category information that is the same as the third product category information of the associated product category information, and then generate the overlap quantity information based on the quantity of all such second product category information.
[0035] In S320, the associated product information corresponding to the largest number of overlapping information is identified as the target product information.
[0036] Specifically, after the terminal device generates the overlap quantity information, the terminal device can determine the associated product information corresponding to the largest overlap quantity information as the target product information.
[0037] For some possible implementations, please refer to [link / reference]. Figure 4 After step S320, the method further includes, but is not limited to, the following steps: In S330, in response to user selection information, the selected product information is obtained.
[0038] Specifically, the terminal device can respond to user selection information and obtain selected product information. The user selection information describes the selection operation made by the target user after learning about the target product information; the selected product information describes the product selected by the target user after learning about the target product information.
[0039] In S340, it is determined whether the selected product information is the same as the target product information.
[0040] Specifically, after the terminal device obtains the selected product information, it can determine whether the selected product information is the same as the target product information.
[0041] In S350, if the selected product information is not the same as the target product information, the push product sequence list information is generated based on the number of overlapping products and multiple related product information.
[0042] Specifically, if the selected product information is not the same as the target product information, it indicates that the target user has not browsed the target product information. Therefore, the terminal device can quickly generate a push product sequence list based on the number of overlapping items and multiple related product information. The push product sequence list describes a list after multiple related product information are sorted in descending order of the number of overlapping items.
[0043] In S360, a re-push instruction is generated based on the product sequence list information.
[0044] Specifically, after the terminal device generates the push product sequence list information, it can generate a push instruction based on the push product sequence list information, which is beneficial for recommending more new products that the target user is interested in.
[0045] For further improvements in recommendation fit, please refer to some possible implementations. Figure 5 After step S350, the method further includes, but is not limited to, the following steps: In S351, the first selection count information of the selected product information is obtained, and based on the preset historical operation database, the second selection count information corresponding to each associated product information in the pushed product sequence table information is obtained.
[0046] Specifically, the terminal device can obtain the first selection count information of the selected product information, and based on the preset historical operation database, obtain the second selection count information corresponding to each associated product information in the pushed product sequence list information. The first selection count information is used to describe the cumulative number of times the selected product information is selected on the e-commerce platform, and the second selection count information is used to describe the cumulative number of times the associated product information is selected on the e-commerce platform.
[0047] In S352, it is determined whether the first selection count information is less than the median among multiple second selection count information.
[0048] Specifically, after the terminal device obtains the first selection count information and the second selection count information, the terminal device can determine whether the first selection count information is less than the median among multiple second selection count information.
[0049] In S353, if the first selection count information is less than the median among multiple second selection count information, then an optimized product sequence list information is generated based on the overlap count information.
[0050] Specifically, if the number of first selections is less than the median of the number of second selections, it indicates that the target user tends to choose products with fewer clicks. Therefore, the terminal device can generate an optimized product sequence list based on the number of overlaps. The optimized product sequence list describes a list of multiple related product information sorted in ascending order of the number of overlaps.
[0051] In S354, an optimized push instruction is generated based on the optimized product sequence list information.
[0052] Specifically, after the terminal device generates the optimized product sequence list information, the terminal device can generate an optimized push instruction based on the optimized product sequence list information. The optimized push instruction is used to instruct the optimized product sequence list information to be accurately pushed to the target user.
[0053] The implementation principle of the precise push method based on the e-commerce platform in this application embodiment is as follows: The terminal device can first obtain the latest browsed products and multiple historical browsed product information of the target user based on the e-commerce platform and the sampling time period. Then, based on the latest browsed products, it can accurately generate multiple related product information corresponding to the latest browsed products. Based on the multiple related product information and multiple historical browsed product information, it can effectively generate target product information. Finally, based on the target product information, it can efficiently generate product push instructions, thereby realizing the precise recommendation of new products of interest to the target user.
[0054] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0055] Embodiments of this application also provide a precise push system based on an e-commerce platform. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 6 As shown, the system 60 includes: The latest browsed product acquisition module 61 is used to acquire the latest browsed products and multiple historical browsed product information of the target user based on a preset e-commerce platform and a preset sampling time period. Related product information generation module 62: Used to generate multiple related product information corresponding to the most recently viewed product; Target product information generation module 63: used to generate target product information based on multiple related product information and multiple historically browsed product information; Product push instruction generation module 64: Used to generate product push instructions based on target product information.
[0056] Optionally, the aforementioned associated product information generation module 62 includes: First Product Category Information Acquisition Submodule: Used to acquire the first product category information of the latest browsed product; The associated product information determination submodule is used to determine multiple associated product information corresponding to the most recently viewed product based on a preset associated product database and the first product category information. The associated product database pre-stores multiple candidate category information, related category information corresponding to each candidate category information, and multiple related product information corresponding to each related category information. The associated product information is used to describe the related product information corresponding to the related category information that is the same as the first product category information.
[0057] Optionally, the system 60 also includes: Second product category information acquisition module: used to acquire second product category information of historically browsed product information, and to acquire third product category information of associated product information; Accordingly, the aforementioned target product information generation module 63 includes: Overlapping Quantity Information Generation Submodule: Used for each associated product information: Based on the associated product information, generate overlapping quantity information, where the overlapping quantity information is used to describe the quantity corresponding to the second product category information that is the same as the third product category information; The target product information determination submodule is used to determine the associated product information corresponding to the largest number of overlapping information as the target product information.
[0058] Optionally, the system 60 also includes: Product Information Acquisition Module: Used to retrieve selected product information in response to user selections; Product Information Selection Module: Used to determine whether the selected product information is the same as the target product information; Push Product Sequence List Information Generation Module: If the selected product information is not the same as the target product information, it generates push product sequence list information based on the number of overlaps and multiple related product information. The push product sequence list information describes a list after sorting multiple related product information in descending order of the number of overlaps. Re-push instruction generation module: Used to generate re-push instructions based on the push product sequence list information.
[0059] Optionally, the system 60 also includes: First Selection Count Information Acquisition Module: Used to acquire the first selection count information of product information, and based on the preset historical operation database, acquire the second selection count information corresponding to each associated product information in the push product sequence table information; First selection count information judgment module: used to determine whether the first selection count information is less than the median among multiple second selection count information; The optimized product sequence list information generation module is used to generate optimized product sequence list information based on the number of overlaps if the first selection count information is less than the median among multiple second selection count information. The optimized product sequence list information describes a list after sorting multiple related product information in ascending order of the number of overlaps. Optimized push notification generation module: Used to generate optimized push notifications based on optimized product sequence list information.
[0060] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.
[0061] This application also provides a terminal device, such as... Figure 7 As shown, the terminal device 70 of this embodiment includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71. When the processor 71 executes the computer program 73, it implements the steps described in the precise push method embodiment above, for example... Figure 1 Steps S100 to S400 are shown; or, when processor 71 executes computer program 73, it implements the functions of each module in the above-described device, for example... Figure 6 The functions of modules 61 to 64 are shown.
[0062] The terminal device 70 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device, and includes, but is not limited to, a processor 71 and a memory 72. Those skilled in the art will understand that... Figure 7 This is merely an example of terminal device 70 and does not constitute a limitation on terminal device 70. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 70 may also include input / output devices, network access devices, buses, etc.
[0063] The processor 71 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.
[0064] The memory 72 can be an internal storage unit of the terminal device 70, such as the hard disk or memory of the terminal device 70. The memory 72 can also be an external storage device of the terminal device 70, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 70. Furthermore, the memory 72 can include both internal storage units and external storage devices of the terminal device 70. The memory 72 can also store computer program 73 and other programs and data required by the terminal device 70. The memory 72 can also be used to temporarily store data that has been output or will be output.
[0065] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.
[0066] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.
Claims
1. A precise push method based on an e-commerce platform, characterized in that, The method includes: Based on a preset e-commerce platform and according to a preset sampling time period, information on the latest browsed products and multiple historical browsed products of the target user is obtained. Based on the most recently viewed product, generate information on multiple associated products corresponding to the most recently viewed product; Based on multiple related product information and multiple historically browsed product information, target product information is generated; Based on the target product information, a product push instruction is generated.
2. The method according to claim 1, characterized in that, The step involves generating multiple associated product information corresponding to the most recently viewed product: Obtain the first product category information of the most recently viewed product; Based on a preset associated product database, multiple associated product information corresponding to the latest browsed product is determined according to the first product category information. The associated product database pre-stores multiple candidate category information, related category information corresponding to each candidate category information, and multiple related product information corresponding to each related category information. The associated product information is used to describe the related product information corresponding to the related category information that is the same as the first product category information.
3. The method according to claim 1, characterized in that, Before generating the target product information based on multiple related product information and multiple historical browsing product information, the method further includes: Obtain the second product category information of the historically browsed product information, and obtain the third product category information of the associated product information; Accordingly, generating target product information based on multiple related product information and multiple historically browsed product information includes: For each of the associated product information: Based on the associated product information, generate overlapping quantity information, wherein the overlapping quantity information is used to describe the quantity corresponding to the second product category information that is the same as the third product category information; The associated product information corresponding to the largest number of overlapping information is determined as the target product information.
4. The method according to claim 3, characterized in that, After determining that the associated product information corresponding to the largest number of overlapping items is the target product information, the method further includes: Responding to user selections, obtain information about the selected products; Determine whether the selected product information is the same as the target product information; If the selected product information is not the same as the target product information, then based on the overlap quantity information, a push product sequence list is generated according to the multiple associated product information, wherein the push product sequence list is used to describe a list after sorting the multiple associated product information in descending order of the overlap quantity information; Based on the product sequence list information, a re-push instruction is generated.
5. The method according to claim 4, characterized in that, After generating a push product sequence list based on the overlap quantity information and multiple related product information if the selected product information is not the same as the target product information, the method further includes: Obtain the first selection count information of the selected product information, and based on the preset historical operation database, obtain the second selection count information corresponding to each associated product information in the pushed product sequence table information; Determine whether the first selection count information is less than the median among multiple second selection count information; If the first selection count information is less than the median among multiple second selection count information, then an optimized product sequence list information is generated based on the overlap count information, wherein the optimized product sequence list information is used to describe a list after sorting multiple related product information in ascending order of the overlap count information; Based on the optimized product sequence information, an optimized push instruction is generated.
6. A precision push system based on an e-commerce platform, characterized in that, The system includes: The latest viewed products acquisition module is used to acquire the latest viewed products and multiple historical viewed products information of target users based on a preset e-commerce platform and a preset sampling time period. Related product information generation module: used to generate multiple related product information corresponding to the latest viewed product based on the latest viewed product; Target product information generation module: used to generate target product information based on multiple related product information and multiple historically browsed product information; Product push instruction generation module: used to generate product push instructions based on the target product information.
7. The system according to claim 6, characterized in that, The associated product information generation module includes: First Product Category Information Acquisition Submodule: Used to acquire the first product category information of the latest browsed product; The associated product information determination submodule is used to determine multiple associated product information corresponding to the latest browsed product based on a preset associated product database and the first product category information. The associated product database pre-stores multiple candidate category information, related category information corresponding to each candidate category information, and multiple related product information corresponding to each related category information. The associated product information is used to describe the related product information corresponding to the related category information that is the same as the first product category information.
8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.