E-commerce data processing method and system based on Internet

Abstract

The invention relates to an internet-based e-commerce data processing method and system, and the method comprises the steps: obtaining the actual operation process data of a current consumption recommendation sending main body in a current product display interface of a current operation application, obtaining a current product recommendation instruction, and generating the current recommended product data; setting the current recommended product data, generating modeled recommended product display data, and generating a current recommended product link; receiving product recommendation feedback data, generating a feedback data display interface, obtaining actual trigger data, judging whether the current consumption recommendation sending main body views the product recommendation feedback data or not, if not, generating a current prompt application according to the current operation application, and displaying the current prompt application according to the current operation application. The current prompting application is used for prompting the current consumption recommendation sending main body. According to the method, the accuracy in the data sharing and recommendation process is improved, and rapid data receiving and information browsing efficiency of an information receiver are facilitated.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and in particular to an Internet-based e-commerce data processing method and system. Background Technology

[0002] Once a user makes a purchase on an e-commerce website, they transform from a potential customer into a valuable customer. E-commerce websites typically store user transaction information, including purchase time, purchased items, quantity, and payment amount, in their databases; this data constitutes e-commerce data.

[0003] Currently, there are various methods for processing e-commerce data, such as application number...

[0004] Chinese patent CN202211365629.7 discloses a data processing method and related apparatus based on orders. The method is applied to a store management server in an e-commerce system for managing store data of a target store. The e-commerce system includes an e-commerce platform server, a store management server, and user devices associated with seller user accounts linked to the target store. The method obtains first sales data of pending orders from the e-commerce platform server; determines that there are paid historical orders for the target product corresponding to the pending orders, and then estimates second sales data of the pending orders based on the paid historical orders; if there are no paid historical orders, obtains the real-time unit price of the target product and estimates second sales data based on the real-time unit price; receives and responds to requests from the user device for obtaining the first and second sales data; and pushes the first and second sales data to the user device.

[0005] While the above technical solutions enable sellers to obtain sales data for orders awaiting payment in a timely manner, they have significant limitations. When recommending products during use, providing only one link can lead to data recommendations that do not align with user habits, resulting in low data utilization. Summary of the Invention

[0006] Therefore, it is necessary to provide an internet-based e-commerce data processing method and system that can improve the accuracy of data sharing and recommendation processes, and facilitate the rapid data reception and information browsing efficiency of information recipients, in response to the aforementioned technical problems.

[0007] The technical solution of this invention is as follows:

[0008] An internet-based e-commerce data processing method, the method comprising:

[0009] Based on a preset internet information collection port, the system acquires actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application; it acquires the current product recommendation instruction issued by the current consumer recommendation sending entity; and generates current recommended product data based on the actual operation process data according to the current product recommendation instruction. Based on the information recommendation display mode preset by the current consumer recommendation sending entity, it sets the current recommended product data and generates patterned recommended product display data, and generates a current recommended product link based on the patterned recommended product display data, and sends the current recommended product link to the consumer product recommendation receiving entity. The system then receives feedback from the consumer product recommendation receiving entity regarding the consumer product recommendation. The system receives product recommendation feedback data from the receiving entity and generates a feedback data display interface based on this data. This interface is used to display the product recommendation feedback data when the current consumer recommendation sending entity triggers the current operation application. The system also acquires the actual trigger data of the current consumer recommendation sending entity on the current operation application after receiving the product recommendation feedback data, and determines whether the current consumer recommendation sending entity has viewed the product recommendation feedback data based on this data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operation application. This current prompt application is used to prompt the current consumer recommendation sending entity.

[0010] Specifically, based on a preset internet information collection port, the system acquires actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application, acquires the current product recommendation instruction issued by the current consumer recommendation sending entity, and generates current recommended product data based on the current product recommendation instruction and the actual operation process data; specifically including:

[0011] Based on a preset internet information collection port, the initial operation process data of the current consumer recommendation sending entity on the current product display interface is collected, and an operation data extraction instruction is obtained; according to the operation data extraction instruction, the initial operation process data is extracted to obtain multiple initial operation interfaces; according to the operation data extraction instruction, preset control monitoring permission data is obtained, wherein the control monitoring permission data includes multiple preset operation interfaces; each preset operation interface in the control monitoring permission data is compared with each initial operation interface, and the initial operation interface that matches the preset operation interface is removed, and the remaining initial operation interfaces are packaged to generate actual operation process data; the initial operation process data is obtained. The system generates a current product recommendation instruction from the current consumer recommendation sending entity, and obtains a pre-set data collection duration based on the instruction, wherein the time point at which the instruction is issued is the current initial time point; a data collection period is generated based on the current initial time point and the data collection duration, wherein the data collection period is the time segment starting from the current initial time point and extending backward by the data collection duration; data is collected from the actual operation process data according to the data collection period, and data within the data collection period is generated and set as the current recommended product data.

[0012] Specifically, the information recommendation and display modes include an information content coloring mode and an information content magnification mode;

[0013] Based on the preset information recommendation display mode of the current consumer recommendation sending entity, the current recommended product data is set and patterned recommended product display data is generated. Then, a current recommended product link is generated based on the patterned recommended product display data, and the current recommended product link is sent to the consumer product recommendation receiving entity; specifically including:

[0014] Based on the preset information content coloring mode of the current consumer recommendation sending entity, obtain the corresponding current actual coloring; set the coloring of the current recommended product data according to the current actual coloring, and generate colored product display data; based on the preset information content magnification mode of the current consumer recommendation sending entity, obtain the corresponding information magnification factor; magnify the colored product display data according to the information magnification factor and generate patterned recommended product display data; generate the current recommended product link according to the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity.

[0015] Specifically, the process involves acquiring product recommendation feedback data from the recipient of the consumer product recommendation, generating a feedback data display interface based on the product recommendation feedback data, and displaying the product recommendation feedback data based on the feedback data display interface; this specifically includes:

[0016] The system acquires product recommendation feedback data from the consumer product recommendation recipient, and splits the product recommendation feedback data according to time nodes to generate refined split data. It then sorts the refined split data according to time nodes to generate an initial sorted data table. Next, it acquires the key display data markers set by the current consumer recommendation sender. Based on the key display data markers, it indexes the refined split data in the initial sorted data table and acquires target index data. Finally, it adjusts the sorting of the refined split data in the initial sorted data table based on the target index data, and generates final sorted display data after the sorting adjustment is completed. Finally, it generates a feedback data display interface based on the final sorted display data and displays the product recommendation feedback data based on the feedback data display interface.

[0017] Specifically, after receiving the product recommendation feedback data, the system acquires the actual trigger data of the current consumer recommendation sending entity on the current operating application, and determines whether the current consumer recommendation sending entity has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operating application. The current prompt application is used to prompt the current consumer recommendation sending entity. Specifically, this includes:

[0018] After receiving the product recommendation feedback data, the system acquires the actual trigger data of the current consumer recommendation sending entity on the current operating application, and extracts the actual number of times the current consumer recommendation sending entity triggers the current product display interface during the triggering process of the current operating application based on the actual trigger data. If the actual number of triggers is greater than or equal to a preset standard trigger threshold, it is determined that the current consumer recommendation sending entity has viewed the product recommendation feedback data, and a data processing completion indication is generated. If the actual number of triggers is less than the preset standard trigger threshold, it is determined that the current consumer recommendation sending entity has not viewed the product recommendation feedback data. The system checks and generates operation prompts; it obtains historical time data of the current consumption recommendation sending entity's use of the current prompt application based on the operation prompts, wherein the historical time data includes multiple historical usage time points; it statistically analyzes each of the historical usage time points and calculates and generates a current predicted usage time range, while simultaneously generating an application interface zoom-in instruction based on the operation prompts; it obtains a preset interface zoom factor based on the application interface zoom factor; it zooms in on the interface of the current operation application based on the interface zoom factor and generates a current prompt application; within the current predicted usage time range, it displays the current prompt application in a preset application prompt area to prompt the current consumption recommendation sending entity.

[0019] Specifically, an internet-based e-commerce data processing system includes:

[0020] The recommendation data generation module is used to obtain the actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application based on a preset Internet information collection port, obtain the current product recommendation instruction made by the current consumer recommendation sending entity, and generate current recommended product data based on the current product recommendation instruction and the actual operation process data.

[0021] The recommended product sending module is used to set the current recommended product data based on the information recommendation display mode preset by the current consumer recommendation sending entity and generate patterned recommended product display data, generate the current recommended product link based on the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity;

[0022] The feedback data receiving module is used to receive product recommendation feedback data from the consumer product recommendation receiving subject to the consumer product recommendation receiving subject, and generate a feedback data display interface based on the product recommendation feedback data. The feedback data display interface is used to display the product recommendation feedback data when the current consumer recommendation sending subject triggers the current operation application.

[0023] The feedback data reminder module is used to acquire the actual trigger data of the current consumption recommendation sending entity to the current operation application after receiving the product recommendation feedback data, and to determine whether the current consumption recommendation sending entity has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operation application. The current prompt application is used to prompt the current consumption recommendation sending entity.

[0024] Specifically, the recommendation data generation module is also used for:

[0025] Based on a preset internet information collection port, the initial operation process data of the current consumer recommendation sending entity on the current product display interface is collected, and an operation data extraction instruction is obtained; according to the operation data extraction instruction, the initial operation process data is extracted to obtain multiple initial operation interfaces; according to the operation data extraction instruction, preset control monitoring permission data is obtained, wherein the control monitoring permission data includes multiple preset operation interfaces; each preset operation interface in the control monitoring permission data is compared with each initial operation interface, and the initial operation interface that matches the preset operation interface is removed, and the remaining initial operation interfaces are packaged to generate actual operation process data; the initial operation process data is obtained. The system generates a current product recommendation instruction from the current consumer recommendation sending entity, and obtains a pre-set data collection duration based on the instruction, wherein the time point at which the instruction is issued is the current initial time point; a data collection period is generated based on the current initial time point and the data collection duration, wherein the data collection period is the time segment starting from the current initial time point and extending backward by the data collection duration; data is collected from the actual operation process data based on the data collection period, and data within the data collection period is generated and set as the current recommended product data;

[0026] The information recommendation display mode includes an information content coloring mode and an information content magnification mode; the recommended product sending module is further configured to: obtain the corresponding current actual coloring based on the information content coloring mode preset by the current consumer recommendation sending entity; set the coloring of the current recommended product data according to the current actual coloring and generate colored product display data; obtain the corresponding information magnification factor based on the information content magnification mode preset by the current consumer recommendation sending entity; magnify the colored product display data according to the information magnification factor and generate patterned recommended product display data; generate a current recommended product link according to the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity.

[0027] Specifically, the feedback data receiving module is also used for:

[0028] The system acquires product recommendation feedback data from the consumer product recommendation recipient, and splits the product recommendation feedback data according to time nodes to generate detailed split data; sorts the detailed split data according to time nodes to generate an initial sorted data table; acquires the key display data markers set by the current consumer recommendation sender; indexes the detailed split data in the initial sorted data table according to the key display data markers and acquires target index data; adjusts the sorting of the detailed split data in the initial sorted data table according to the target index data, and generates final sorted display data after the sorting adjustment is completed; generates a feedback data display interface based on the final sorted display data, and displays the product recommendation feedback data based on the feedback data display interface;

[0029] The feedback data reminder module is further configured to: acquire the actual trigger data of the current consumer recommendation sending entity on the current operating application after receiving the product recommendation feedback data, and extract the actual number of times the current consumer recommendation sending entity triggers the current product display interface during the triggering process of the current operating application based on the actual trigger data; if it is determined whether the actual trigger number is greater than or equal to a preset standard trigger threshold; if it is determined that the actual trigger number is greater than or equal to the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has viewed the product recommendation feedback data, and a data processing completion indication is generated; if it is determined that the actual trigger number is less than the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has not viewed the product recommendation feedback data. The system displays product recommendation feedback data and generates operation prompts. Based on these prompts, it retrieves historical usage data of the current consumer recommendation sender using the current prompt application, including multiple historical usage time points. It then statistically analyzes each historical usage time point and calculates a current predicted usage time range. Simultaneously, it generates an application interface zoom-in command based on the operation prompts. A preset zoom level is obtained based on the zoom level. The interface of the currently used application is zoomed in according to the zoom level, and a current prompt application is generated. Within the current predicted usage time range, the current prompt application is displayed in a preset application prompt area to alert the current consumer recommendation sender.

[0030] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps described in the Internet-based e-commerce data processing method.

[0031] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps described in the Internet-based e-commerce data processing method.

[0032] The technical effects achieved by this invention are as follows:

[0033] The aforementioned internet-based e-commerce data processing method and system sequentially acquires actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application through a preset internet information collection port; acquires the current product recommendation instruction issued by the current consumer recommendation sending entity; generates current recommended product data based on the actual operation process data according to the current product recommendation instruction; sets the current recommended product data according to the preset information recommendation display mode of the current consumer recommendation sending entity and generates patterned recommended product display data; generates a current recommended product link according to the patterned recommended product display data; and sends the current recommended product link to the consumer product recommendation receiving entity; receives product recommendation feedback data from the consumer product recommendation receiving entity; and generates feedback data display based on the product recommendation feedback data. The interface, specifically the feedback data display interface, is used to display product recommendation feedback data when the current consumer recommendation sending entity triggers the current operation application. It acquires the actual trigger data of the current consumer recommendation sending entity on the current operation application after receiving the product recommendation feedback data, and determines whether the current consumer recommendation sending entity has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operation application. The current prompt application is used to prompt the current consumer recommendation sending entity. Compared to the existing sharing method that only shares a single link, this improves the utilization rate of e-commerce data, specifically by improving the data utilization rate of the actual operation process data, enhancing the accuracy of data sharing and recommendation processes, and facilitating faster data reception and information browsing efficiency for the information recipient. Attached Figure Description

[0034] Figure 1 This is a flowchart illustrating an internet-based e-commerce data processing method in one embodiment.

[0035] Figure 2 This is a structural block diagram of an internet-based e-commerce data processing system in one embodiment;

[0036] Figure 3 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0038] In one embodiment, a terminal is provided. The terminal is configured to acquire actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application based on a preset internet information collection port; acquire the current product recommendation instruction issued by the current consumer recommendation sending entity; generate current recommended product data based on the current product recommendation instruction and the actual operation process data; set the current recommended product data according to a preset information recommendation display mode of the current consumer recommendation sending entity and generate patterned recommended product display data; generate a current recommended product link based on the patterned recommended product display data; and send the current recommended product link to the consumer product recommendation receiving entity; and receive the consumer product recommendation. The system receives product recommendation feedback data from the receiving entity and generates a feedback data display interface based on this data. This interface is used to display the product recommendation feedback data when the current consumer recommendation sending entity triggers the current operation application. The system also acquires the actual trigger data of the current consumer recommendation sending entity on the current operation application after receiving the product recommendation feedback data and determines whether the current consumer recommendation sending entity has viewed the product recommendation feedback data. If yes, a data processing completion indication is generated; otherwise, a current prompt application is generated based on the current operation application. This current prompt application is used to prompt the current consumer recommendation sending entity.

[0039] The terminal may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices.

[0040] In one embodiment, such as Figure 1 As shown, an internet-based e-commerce data processing method is provided, the method comprising:

[0041] Step S100: Based on a preset Internet information collection port, obtain the actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application, obtain the current product recommendation instruction made by the current consumer recommendation sending entity, and generate current recommended product data based on the actual operation process data according to the current product recommendation instruction;

[0042] In this embodiment, the operation information of the current consumer recommendation sender is collected by setting up the internet information collection port. The current operation application is an e-commerce related shopping app, including but not limited to Taobao, Pinduoduo, JD.com, and Vipshop. By setting up the internet information collection port, information about the current consumer recommendation sender can be quickly collected and uploaded to the terminal.

[0043] Furthermore, the Internet information collection port can be a screen recording and browsing module built into the terminal. This screen recording and browsing module is used to record the operation steps, operation selections, and operation pauses when the current consumer recommendation sending entity operates, which is the actual operation process data.

[0044] Step S200: Based on the preset information recommendation display mode of the current consumer recommendation sending entity, set the current recommended product data and generate patterned recommended product display data, generate the current recommended product link according to the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity;

[0045] Step S300: Receive product recommendation feedback data from the consumer product recommendation recipient to the consumer product recommendation recipient, and generate a feedback data display interface based on the product recommendation feedback data. The feedback data display interface is used to display the product recommendation feedback data when the current consumer recommendation sending subject triggers the current operation application.

[0046] Step S400: After receiving the product recommendation feedback data, obtain the actual trigger data of the current consumption recommendation sending subject to the current operation application, and determine whether the current consumption recommendation sending subject has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, generate a data processing completion indication. If the determination is no, generate a current prompt application based on the current operation application. The current prompt application is used to prompt the current consumption recommendation sending subject.

[0047] In this embodiment, the current recommended product data is set based on the information recommendation display mode preset by the current consumer recommendation sending entity, and patterned recommended product display data is generated. A current recommended product link is generated based on the patterned recommended product display data, and the current recommended product link is sent to the consumer product recommendation receiving entity. Feedback data on product recommendations from the consumer product recommendation receiving entity is received, and a feedback data display interface is generated based on the product recommendation feedback data. This feedback data display interface is used to display the product recommendation feedback data when the current consumer recommendation sending entity triggers the current operation application. The actual trigger data of the current consumer recommendation sending entity on the current operation application after receiving the product recommendation feedback data is obtained, and a judgment is made based on the actual trigger data. The system determines whether the current consumer recommendation sender has viewed the product recommendation feedback data. If yes, a data processing completion indication is generated; if no, a current prompt application is generated based on the current operation application. This current prompt application is used to prompt the current consumer recommendation sender. When the current consumer recommendation sender needs to make a recommendation, the system highlights the detailed content within the overall product content that the user wants to share, thus enabling the consumer product recommendation recipient to know the content the current consumer recommendation sender wants to share. Compared to the existing sharing method that only shares a link, this improves the utilization rate of e-commerce data. Specifically, it improves the data utilization rate of the actual operation process data, enhances the accuracy of data sharing and recommendation, and facilitates faster data reception and information browsing efficiency for the information recipient.

[0048] In one embodiment, step S100: Obtain actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application based on a preset Internet information collection port; obtain the current product recommendation instruction issued by the current consumer recommendation sending entity; and generate current recommended product data based on the actual operation process data according to the current product recommendation instruction; specifically including:

[0049] Step S110: Collect the initial operation process data of the current consumer recommendation sending entity on the current product display interface based on the preset Internet information collection port, and obtain the operation data extraction instruction;

[0050] Step S120: Extract the interface from the initial operation process data according to the operation data extraction instruction and obtain multiple initial operation interfaces;

[0051] Step S130: Obtain preset operation monitoring permission data according to the operation data extraction instruction, wherein the operation monitoring permission data includes multiple preset operation interfaces;

[0052] Step S140: Compare each of the preset operation interfaces in the control monitoring permission data with each of the initial operation interfaces, remove the initial operation interfaces that match the preset operation interfaces, and package the remaining initial operation interfaces to generate actual operation process data.

[0053] In this embodiment, to achieve detailed and confidential data collection and protect the privacy of the current consumer recommendation sender, the system first collects overall data, specifically the initial operation process data of the current consumer recommendation sender on the current product display interface based on a preset internet information collection port, and obtains operation data extraction instructions. Then, it performs detailed data breakdown to obtain the interfaces involved in the current operation. Specifically, it extracts interfaces from the initial operation process data according to the operation data extraction instructions to obtain multiple initial operation interfaces. To prevent the privacy data of the current consumer recommendation sender from being uncollected and unused, it obtains preset control monitoring permission data according to the operation data extraction instructions. This control monitoring permission data includes multiple preset operation interfaces. Then, it compares each preset operation interface in the control monitoring permission data with each initial operation interface and removes initial operation interfaces that match the preset operation interfaces. The remaining initial operation interfaces are then packaged to generate actual operation process data, thereby achieving data privacy collection.

[0054] Step S150: Obtain the current product recommendation instruction issued by the current consumer recommendation sending entity, and obtain the data collection duration preset by the current consumer recommendation sending entity according to the current product recommendation instruction, wherein the time point at which the current consumer recommendation sending entity issues the current product recommendation instruction is the current initial time point;

[0055] Step S160: Generate a data collection time period based on the current initial time point and the data collection duration, wherein the data collection time period is a time period formed by taking the current initial time point as the starting point and extending forward by the data collection duration;

[0056] Step S170: Collect data from the actual operation process data according to the data collection time period and generate data within the data collection time period, and set it as the current recommended product data.

[0057] In this embodiment, in order to improve the reliability of the data and to align with the actual browsing habits of the current consumer recommendation sender, and considering that the content browsed by the current consumer recommendation sender within a specific time period before sharing is the content that the consumer product recommendation recipient wants to know, the accuracy of data sharing is improved by collecting current recommended product data. Specifically, the process involves first obtaining the current product recommendation instruction issued by the current consumer recommendation sending entity, and then obtaining the data collection duration preset by the current consumer recommendation sending entity based on the current product recommendation instruction. The time point at which the current consumer recommendation sending entity issues the current product recommendation instruction is the current initial time point. Then, a data collection period is generated based on the current initial time point and the data collection duration. This data collection period is the time segment formed by taking the current initial time point as the starting point and extending it forward by the data collection duration. For example, if the current initial time point is 7:00 AM and the preset data collection duration is 2 minutes, then when generating the data collection period, the time segment is formed by taking 7:00 AM as the starting point and extending it forward by 2 minutes. That is, the data collection period is the data generated by the operations performed by the current consumer recommendation sending entity during the period from 6:58 AM to 7:00 AM. This ensures the validity of both the time and the data, improving data utilization efficiency.

[0058] Finally, data is collected from the actual operation process data according to the data collection time period, and data within the data collection time period is generated and set as the current recommended product data.

[0059] In one embodiment, the information recommendation display mode includes an information content coloring mode and an information content magnification mode;

[0060] Step S200: Based on the preset information recommendation display mode of the current consumer recommendation sending entity, set the current recommended product data and generate patterned recommended product display data, generate the current recommended product link according to the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity; specifically including:

[0061] Step S210: Obtain the corresponding current actual coloring based on the preset information content coloring mode of the current consumption recommendation sending subject;

[0062] Step S220: Set the coloring of the current recommended product data according to the current actual coloring, and generate the colored product display data;

[0063] Step S230: Obtain the corresponding information magnification factor based on the preset information content magnification mode of the current consumption recommendation sending entity;

[0064] Step S240: Magnify the colored product display data based on the information magnification factor and generate patterned recommended product display data;

[0065] Step S250: Generate a current recommended product link based on the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity.

[0066] In this embodiment, to highlight the relevant data, the corresponding current actual coloring is obtained based on the information content coloring mode preset by the current consumer recommendation sending entity. Then, the current recommended product data is colored according to the current actual coloring, and colored product display data is generated. Next, the corresponding information magnification factor is obtained based on the information content magnification mode preset by the current consumer recommendation sending entity. Finally, the colored product display data is magnified based on the information magnification factor, and patterned recommended product display data is generated. In this way, a current recommended product link is generated based on the patterned recommended product display data, and the current recommended product link is sent to the consumer product recommendation receiving entity. Compared with the prior art, which only shares the link without specifically highlighting a certain part of the data, causing the consumer product recommendation receiving entity to not know which part of the content to view, this application achieves coloring and magnification processing of detailed data through information content coloring mode and information content magnification mode, so that the part of the information operated by the current consumer recommendation sending entity can be clearly known by the consumer product recommendation receiving entity.

[0067] In one embodiment, step S300 involves: obtaining product recommendation feedback data from the consumer product recommendation recipient, generating a feedback data display interface based on the product recommendation feedback data, and displaying the product recommendation feedback data based on the feedback data display interface; specifically including:

[0068] Step S310: Obtain the product recommendation feedback data from the consumer product recommendation recipient to the consumer product recommendation recipient, and split the product recommendation feedback data according to time nodes to generate detailed split data;

[0069] Step S320: Sort the refined split data according to the time nodes and generate an initial sorted data table;

[0070] Step S330: Obtain the key display data markers set by the current consumer recommendation sending entity;

[0071] Step S340: Index the refined split data in the initial sorted data table according to the highlighted data tags, and obtain the target index data;

[0072] Step S350: Sort and adjust the refined split data in the initial sorting data table according to the target index data, and generate the final sorting display data after the sorting adjustment is completed;

[0073] Step S360: Generate a feedback data display interface based on the final sorted display data, and display the product recommendation feedback data based on the feedback data display interface.

[0074] In this embodiment, to improve the data display effect, the refined data is sorted according to time nodes to generate an initial sorted data table; the key display data markers set by the current consumer recommendation sending entity are obtained; and to perform precise refined sorting of the data, the refined data in the initial sorted data table is indexed according to the key display data markers to obtain target index data; the refined data in the initial sorted data table is sorted and adjusted according to the target index data, and a final sorted display data is generated after the sorting adjustment is completed; a feedback data display interface is generated based on the final sorted display data, and the product recommendation feedback data is displayed based on the feedback data display interface, thereby achieving reliable data display and improving data utilization efficiency.

[0075] In one embodiment, step S400: Obtain the actual trigger data of the current consumer recommendation sending entity on the current operating application after receiving the product recommendation feedback data, and determine whether the current consumer recommendation sending entity has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompting application is generated based on the current operating application. The current prompting application is used to prompt the current consumer recommendation sending entity. Specifically, this includes:

[0076] Step S410: Obtain the actual trigger data of the current consumption recommendation sending entity on the current operation application after receiving the product recommendation feedback data, and extract the actual number of times the current consumption recommendation sending entity triggers the current product display interface during the triggering process of the current operation application based on the actual trigger data;

[0077] Step S420: Determine whether the actual number of triggers is greater than or equal to a preset standard trigger threshold;

[0078] Step S430: If it is determined that the actual number of triggers is greater than or equal to the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has viewed the product recommendation feedback data, and a data processing completion indication is generated;

[0079] Step S440: If the actual number of triggers is less than the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has not viewed the product recommendation feedback data, and an operation prompt instruction is generated;

[0080] In this embodiment, to ensure that the current consumer recommendation sending entity can view the feedback data promptly, a design is adopted that determines whether it has viewed the feedback data before proceeding with subsequent processing. Specifically, the actual trigger data of the current consumer recommendation sending entity on the current operating application after receiving the product recommendation feedback data is first obtained. Based on the actual trigger data, the actual number of times the current consumer recommendation sending entity triggers the current product display interface during the triggering process on the current operating application is extracted. The standard trigger threshold can be set to 0, meaning that as long as a trigger value greater than or equal to the preset standard trigger threshold is detected, it can be determined that the current consumer recommendation sending entity has viewed the product recommendation feedback data, and a data processing completion indication is generated. In this embodiment, the current operating application is pre-set to display the product recommendation feedback data whenever it is triggered. Next, if it is determined that the actual trigger count is less than the preset standard trigger threshold, it is determined that the current consumer recommendation sending entity has not viewed the product recommendation feedback data, and an operation prompt instruction is generated.

[0081] Step S450: Obtain historical time data of the current consumption recommendation sending subject using the current prompt application according to the operation prompt instruction, wherein the historical time data includes multiple historical usage time points;

[0082] Step S460: Statistically analyze each of the historical usage time points and calculate the current predicted usage time range. At the same time, generate an application interface zoom-in instruction based on the operation prompt instructions.

[0083] Step S470: Obtain the preset interface magnification factor according to the application interface magnification command;

[0084] Step S480: Zoom in on the interface of the currently operating application according to the zoom level and generate the current prompt application;

[0085] Step S490: Within the current predicted usage time range, display the current prompt application in a preset application prompt area to prompt the current consumption recommendation sending entity.

[0086] In this embodiment, to improve the convenience of data processing for the current consumer recommendation sending entity, historical time data of the current consumer recommendation sending entity's use of the current prompt application is first obtained according to the operation prompt instruction. This historical time data includes multiple historical usage time points. Then, the historical usage time points are statistically analyzed, and a current predicted usage time range is calculated. When multiple historical usage time points are obtained, the historical usage time point with the most occurrences is selected, and a range is generated based on these points. Finally, the current predicted usage time range is generated. To improve data browsing efficiency, an application interface magnification instruction is simultaneously generated according to the operation prompt instruction. A preset interface magnification factor is obtained based on the application interface magnification instruction. The interface of the current operation application is then magnified according to the interface magnification factor, and the current prompt application is generated. Finally, the current prompt application is displayed in a preset application prompt area within the current predicted usage time range to prompt the current consumer recommendation sending entity, thereby achieving timely data reminder processing.

[0087] In one embodiment, such as Figure 2 As shown, an internet-based e-commerce data processing system includes:

[0088] The recommendation data generation module is used to obtain the actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application based on a preset Internet information collection port, obtain the current product recommendation instruction made by the current consumer recommendation sending entity, and generate current recommended product data based on the current product recommendation instruction and the actual operation process data.

[0089] The recommended product sending module is used to set the current recommended product data based on the information recommendation display mode preset by the current consumer recommendation sending entity and generate patterned recommended product display data, generate the current recommended product link based on the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity;

[0090] The feedback data receiving module is used to receive product recommendation feedback data from the consumer product recommendation receiving subject to the consumer product recommendation receiving subject, and generate a feedback data display interface based on the product recommendation feedback data. The feedback data display interface is used to display the product recommendation feedback data when the current consumer recommendation sending subject triggers the current operation application.

[0091] The feedback data reminder module is used to acquire the actual trigger data of the current consumption recommendation sending entity to the current operation application after receiving the product recommendation feedback data, and to determine whether the current consumption recommendation sending entity has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operation application. The current prompt application is used to prompt the current consumption recommendation sending entity.

[0092] In one embodiment, the recommendation data generation module is further configured to:

[0093] Based on a preset internet information collection port, the initial operation process data of the current consumer recommendation sending entity on the current product display interface is collected, and an operation data extraction instruction is obtained; according to the operation data extraction instruction, the initial operation process data is extracted to obtain multiple initial operation interfaces; according to the operation data extraction instruction, preset control monitoring permission data is obtained, wherein the control monitoring permission data includes multiple preset operation interfaces; each preset operation interface in the control monitoring permission data is compared with each initial operation interface, and the initial operation interface that matches the preset operation interface is removed, and the remaining initial operation interfaces are packaged to generate actual operation process data; the initial operation process data is obtained. The system generates a current product recommendation instruction from the current consumer recommendation sending entity, and obtains a pre-set data collection duration based on the instruction, wherein the time point at which the instruction is issued is the current initial time point; a data collection period is generated based on the current initial time point and the data collection duration, wherein the data collection period is the time segment starting from the current initial time point and extending backward by the data collection duration; data is collected from the actual operation process data based on the data collection period, and data within the data collection period is generated and set as the current recommended product data;

[0094] The information recommendation display mode includes an information content coloring mode and an information content magnification mode; the recommended product sending module is further configured to: obtain the corresponding current actual coloring based on the information content coloring mode preset by the current consumer recommendation sending entity; set the coloring of the current recommended product data according to the current actual coloring and generate colored product display data; obtain the corresponding information magnification factor based on the information content magnification mode preset by the current consumer recommendation sending entity; magnify the colored product display data according to the information magnification factor and generate patterned recommended product display data; generate a current recommended product link according to the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity.

[0095] In one embodiment, the feedback data receiving module is further configured to:

[0096] The system acquires product recommendation feedback data from the consumer product recommendation recipient, and splits the product recommendation feedback data according to time nodes to generate detailed split data; sorts the detailed split data according to time nodes to generate an initial sorted data table; acquires the key display data markers set by the current consumer recommendation sender; indexes the detailed split data in the initial sorted data table according to the key display data markers and acquires target index data; adjusts the sorting of the detailed split data in the initial sorted data table according to the target index data, and generates final sorted display data after the sorting adjustment is completed; generates a feedback data display interface based on the final sorted display data, and displays the product recommendation feedback data based on the feedback data display interface;

[0097] The feedback data reminder module is further configured to: acquire the actual trigger data of the current consumer recommendation sending entity on the current operating application after receiving the product recommendation feedback data, and extract the actual number of times the current consumer recommendation sending entity triggers the current product display interface during the triggering process of the current operating application based on the actual trigger data; if it is determined whether the actual trigger number is greater than or equal to a preset standard trigger threshold; if it is determined that the actual trigger number is greater than or equal to the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has viewed the product recommendation feedback data, and a data processing completion indication is generated; if it is determined that the actual trigger number is less than the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has not viewed the product recommendation feedback data. The system displays product recommendation feedback data and generates operation prompts. Based on these prompts, it retrieves historical usage data of the current consumer recommendation sender using the current prompt application, including multiple historical usage time points. It then statistically analyzes each historical usage time point and calculates a current predicted usage time range. Simultaneously, it generates an application interface zoom-in command based on the operation prompts. A preset zoom level is obtained based on the zoom level. The interface of the currently used application is zoomed in according to the zoom level, and a current prompt application is generated. Within the current predicted usage time range, the current prompt application is displayed in a preset application prompt area to alert the current consumer recommendation sender.

[0098] In one embodiment, such as Figure 3As shown, a computer device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps described in the above-mentioned Internet-based e-commerce data processing method.

[0099] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps described in the Internet-based e-commerce data processing method.

[0100] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0101] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0102] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. An internet-based e-commerce data processing method, characterized in that, The method includes: Based on a preset internet information collection port, the system acquires actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application; it acquires the current product recommendation instruction issued by the current consumer recommendation sending entity; and generates current recommended product data based on the actual operation process data according to the current product recommendation instruction. Based on the information recommendation display mode preset by the current consumer recommendation sending entity, it sets the current recommended product data and generates patterned recommended product display data, and generates a current recommended product link based on the patterned recommended product display data, and sends the current recommended product link to the consumer product recommendation receiving entity. The system then receives feedback from the consumer product recommendation receiving entity regarding the consumer product recommendation. The system receives product recommendation feedback data from the receiving entity and generates a feedback data display interface based on this data. This interface is used to display the product recommendation feedback data when the current consumer recommendation sending entity triggers the current operation application. The system also acquires the actual trigger data of the current consumer recommendation sending entity on the current operation application after receiving the product recommendation feedback data, and determines whether the current consumer recommendation sending entity has viewed the product recommendation feedback data based on this data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operation application. This current prompt application is used to prompt the current consumer recommendation sending entity.

2. The internet-based e-commerce data processing method according to claim 1, characterized in that, Based on a preset internet information collection port, the system acquires actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application, acquires the current product recommendation instruction issued by the current consumer recommendation sending entity, and generates current recommended product data based on the actual operation process data according to the current product recommendation instruction; specifically including: Based on a preset internet information collection port, the initial operation process data of the current consumer recommendation sending entity on the current product display interface is collected, and an operation data extraction instruction is obtained; according to the operation data extraction instruction, the initial operation process data is extracted to obtain multiple initial operation interfaces; according to the operation data extraction instruction, preset control monitoring permission data is obtained, wherein the control monitoring permission data includes multiple preset operation interfaces; each preset operation interface in the control monitoring permission data is compared with each initial operation interface, and the initial operation interface that matches the preset operation interface is removed, and the remaining initial operation interfaces are packaged to generate actual operation process data; the initial operation process data is obtained. The system generates a current product recommendation instruction from the current consumer recommendation sending entity, and obtains a pre-set data collection duration based on the instruction, wherein the time point at which the instruction is issued is the current initial time point; a data collection period is generated based on the current initial time point and the data collection duration, wherein the data collection period is the time segment starting from the current initial time point and extending backward by the data collection duration; data is collected from the actual operation process data according to the data collection period, and data within the data collection period is generated and set as the current recommended product data.

3. The internet-based e-commerce data processing method according to claim 1, characterized in that, The information recommendation and display modes include an information content coloring mode and an information content magnification mode; Based on the preset information recommendation display mode of the current consumer recommendation sending entity, the current recommended product data is set and patterned recommended product display data is generated. Then, a current recommended product link is generated based on the patterned recommended product display data, and the current recommended product link is sent to the consumer product recommendation receiving entity; specifically including: Based on the preset information content coloring mode of the current consumer recommendation sending entity, obtain the corresponding current actual coloring; set the coloring of the current recommended product data according to the current actual coloring, and generate colored product display data; based on the preset information content magnification mode of the current consumer recommendation sending entity, obtain the corresponding information magnification factor; magnify the colored product display data according to the information magnification factor and generate patterned recommended product display data; generate the current recommended product link according to the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity.

4. The internet-based e-commerce data processing method according to claim 1, characterized in that, Acquire product recommendation feedback data from the recipient of the consumer product recommendation, generate a feedback data display interface based on the product recommendation feedback data, and display the product recommendation feedback data based on the feedback data display interface; specifically including: The system acquires product recommendation feedback data from the consumer product recommendation recipient, and splits the product recommendation feedback data according to time nodes to generate refined split data. It then sorts the refined split data according to time nodes to generate an initial sorted data table. Next, it acquires the key display data markers set by the current consumer recommendation sender. Based on the key display data markers, it indexes the refined split data in the initial sorted data table and acquires target index data. Finally, it adjusts the sorting of the refined split data in the initial sorted data table based on the target index data, and generates final sorted display data after the sorting adjustment is completed. Finally, it generates a feedback data display interface based on the final sorted display data and displays the product recommendation feedback data based on the feedback data display interface.

5. The internet-based e-commerce data processing method according to claim 1, characterized in that, After receiving the product recommendation feedback data, the system acquires the actual trigger data of the current consumption recommendation sending entity on the current operating application, and determines whether the current consumption recommendation sending entity has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operating application. The current prompt application is used to prompt the current consumption recommendation sending entity. Specifically, this includes: After receiving the product recommendation feedback data, the system acquires the actual trigger data of the current consumer recommendation sending entity on the current operating application, and extracts the actual number of times the current consumer recommendation sending entity triggers the current product display interface during the triggering process of the current operating application based on the actual trigger data. If the actual number of triggers is greater than or equal to a preset standard trigger threshold, it is determined that the current consumer recommendation sending entity has viewed the product recommendation feedback data, and a data processing completion indication is generated. If the actual number of triggers is less than the preset standard trigger threshold, it is determined that the current consumer recommendation sending entity has not viewed the product recommendation feedback data. The system checks and generates operation prompts; it obtains historical time data of the current consumption recommendation sending entity's use of the current prompt application based on the operation prompts, wherein the historical time data includes multiple historical usage time points; it statistically analyzes each of the historical usage time points and calculates and generates a current predicted usage time range, while simultaneously generating an application interface zoom-in instruction based on the operation prompts; it obtains a preset interface zoom factor based on the application interface zoom factor; it zooms in on the interface of the current operation application based on the interface zoom factor and generates a current prompt application; within the current predicted usage time range, it displays the current prompt application in a preset application prompt area to prompt the current consumption recommendation sending entity.

6. An internet-based e-commerce data processing system, characterized in that, The system includes: The recommendation data generation module is used to obtain the actual operation process data of the current consumer recommendation sending entity on the current product display interface of the current operating application based on a preset Internet information collection port, obtain the current product recommendation instruction made by the current consumer recommendation sending entity, and generate current recommended product data based on the current product recommendation instruction and the actual operation process data. The recommended product sending module is used to set the current recommended product data based on the information recommendation display mode preset by the current consumer recommendation sending entity and generate patterned recommended product display data, generate the current recommended product link based on the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity; The feedback data receiving module is used to receive product recommendation feedback data from the consumer product recommendation receiving subject to the consumer product recommendation receiving subject, and generate a feedback data display interface based on the product recommendation feedback data. The feedback data display interface is used to display the product recommendation feedback data when the current consumer recommendation sending subject triggers the current operation application. The feedback data reminder module is used to acquire the actual trigger data of the current consumption recommendation sending entity to the current operation application after receiving the product recommendation feedback data, and to determine whether the current consumption recommendation sending entity has viewed the product recommendation feedback data based on the actual trigger data. If the determination is yes, a data processing completion indication is generated; if the determination is no, a current prompt application is generated based on the current operation application. The current prompt application is used to prompt the current consumption recommendation sending entity.

7. The Internet-based e-commerce data processing system according to claim 6, characterized in that, The recommendation data generation module is also used for: The system collects initial operation data of the current consumer recommendation sending entity on the current product display interface based on a preset Internet information collection port, and obtains operation data extraction instructions; it then extracts the interface from the initial operation data according to the operation data extraction instructions and obtains multiple initial operation interfaces. According to the operation data extraction instruction, preset operation monitoring permission data is obtained, wherein the operation monitoring permission data includes multiple preset operation interfaces; each preset operation interface in the operation monitoring permission data is compared with each initial operation interface, and the initial operation interface that matches the preset operation interface is removed, and the remaining initial operation interfaces are packaged to generate actual operation process data; the current product recommendation instruction made by the current consumer recommendation sending entity is obtained, and the data collection duration preset by the current consumer recommendation sending entity is obtained according to the current product recommendation instruction, wherein the time point at which the current consumer recommendation sending entity makes the current product recommendation instruction is the current initial time point; a data collection time period is generated according to the current initial time point and the data collection duration, wherein the data collection time period is the time period formed by taking the current initial time point as the starting point and extending backward by the data collection duration; the actual operation process data is collected according to the data collection time period, and data within the data collection time period is generated and set as the current recommended product data; The information recommendation display mode includes an information content coloring mode and an information content magnification mode; the recommended product sending module is further configured to: obtain the corresponding current actual coloring based on the information content coloring mode preset by the current consumer recommendation sending entity; set the coloring of the current recommended product data according to the current actual coloring and generate colored product display data; obtain the corresponding information magnification factor based on the information content magnification mode preset by the current consumer recommendation sending entity; magnify the colored product display data according to the information magnification factor and generate patterned recommended product display data; generate a current recommended product link according to the patterned recommended product display data, and send the current recommended product link to the consumer product recommendation receiving entity.

8. The Internet-based e-commerce data processing system according to claim 6, characterized in that, The feedback data receiving module is also used for: Obtain product recommendation feedback data from the consumer product recommendation recipient to the consumer product recommendation recipient, and split the product recommendation feedback data according to time nodes to generate refined split data; sort the refined split data according to time nodes to generate an initial sorted data table; obtain the key display data tags set by the current consumer recommendation sending entity; Index the refined data in the initial sorted data table according to the key data tags, and obtain the target index data; sort and adjust the refined data in the initial sorted data table according to the target index data, and generate the final sorted display data after the sorting adjustment is completed; generate a feedback data display interface according to the final sorted display data, and display the product recommendation feedback data based on the feedback data display interface; The feedback data reminder module is also used to: obtain the actual trigger data of the current consumption recommendation sending subject to the current operation application after receiving the product recommendation feedback data, and extract the actual number of times the current consumption recommendation sending subject triggers the current product display interface during the triggering process of the current operation application based on the actual trigger data; If the actual number of triggers is greater than or equal to a preset standard trigger threshold, and if the actual number of triggers is greater than or equal to the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has viewed the product recommendation feedback data, and a data processing completion indication is generated; if the actual number of triggers is less than the preset standard trigger threshold, then it is determined that the current consumer recommendation sending entity has not viewed the product recommendation feedback data, and an operation prompt instruction is generated; based on the operation prompt instruction, historical time data of the current consumer recommendation sending entity's use of the current prompt application is obtained, wherein the historical time data includes multiple historical usage time points; statistics are performed on each of the historical usage time points, and a current predicted usage time range is calculated, while an application interface magnification instruction is generated based on the operation prompt instruction; a preset interface magnification factor is obtained based on the application interface magnification factor; the interface of the current operating application is magnified based on the interface magnification factor and a current prompt application is generated; within the current predicted usage time range, the current prompt application is displayed in a preset application prompt area to prompt the current consumer recommendation sending entity.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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