Intelligent edge banding information consultation management method and system

Abstract

The present application relates to an intelligent edge strip information consultation management method and system, including obtaining the trigger time point of the inquiry interface in real time, and obtaining the current actual browsing edge strip information; generating the current subject's interested tags, filtering out the standard edge strip question answer data, and recording it as the edge strip information answer data to be displayed; obtaining the edge strip information inquiry history record, filtering out the edge strip historical inquiry answer data that matches the current subject's interested tags, and displaying the edge strip historical inquiry answer data and the edge strip information answer data to be displayed; obtaining the current edge strip inquiry information, and judging whether the current edge strip inquiry information is consistent with the preset correct reply to the edge strip information display; if it is judged that the current edge strip inquiry information is not consistent with the preset correct reply to the edge strip information display, then generating an automatic transfer to manual information inquiry instruction. The present invention realizes efficient inquiry and answering, without the need for the purchaser to actively request manual service, thereby improving the answering efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of edge banding information consultation processing, and in particular to an intelligent edge banding information consultation management method and system. Background Art

[0002] Edge banding is a material used to protect, decorate and beautify the cross section of furniture boards. It can make a piece of furniture show a clear wood grain and colorful overall effect. The main component of PVC edge banding is polyvinyl chloride, which is made through mixing, calendering, vacuum forming and other processes. The product is widely used in furniture, office, kitchen utensils, teaching equipment, civil laboratories, etc. The thickness ranges from 0.3 to 3mm, and the width ranges from 12mm to 80mm. The product has the following main features: smooth surface, no bubbles, no lines, moderate gloss, flat surface and back, uniform thickness, consistent width, reasonable hardness, high elasticity, good quality, strong wear resistance, the color of the side of the edge banding after trimming is close to the surface color, no whitish, good gloss, and the overall color of the finished furniture is coordinated.

[0003] With the increasing development of online sales platforms, edge banding is gradually sold online. When selling online, it is necessary to inquire about edge banding, and customer service needs to answer buyers. However, there are many inquiry and answering systems at present. For example, the invention patent with application number CN201910624052.9 discloses a method and device for allocating customer service. A specific implementation of the method includes: in response to receiving a consultation request including a customer's shopping intention, obtaining a consultation sensitivity portrait library of the customer, wherein the consultation sensitivity portrait library is used to characterize the customer's consultation habits; obtaining customer service information of a candidate customer service group that matches the shopping intention; and selecting customer service from the candidate customer service group whose customer service information matches the consultation sensitivity portrait library.

[0004] Although the above technology can assign customer service to customers based on their inquiry sensitivity profile, thereby improving the conversion efficiency of the customer service system and bringing revenue growth, it is still not smart enough and affects the efficiency of inquiries. Summary of the invention

[0005] Based on this, it is necessary to provide an intelligent edge banding information consultation management method and system that can improve the efficiency of edge banding inquiries in response to the above technical problems.

[0006] The technical solution of the present invention is as follows:

[0007] An intelligent edge banding information consultation management method, the method comprising:

[0008] Acquire in real time the query interface triggering time point when the current query subject triggers the edge strip information query interface, and acquire the current actual browsing edge strip information of the current query subject at the edge strip information introduction interface before the query interface triggering time point; generate a current subject interest tag according to the current actual browsing edge strip information, and filter out standard edge strip question answer data corresponding to the standard question tag matching the current subject interest tag from a preset edge strip information query database based on the current subject interest tag, and record the standard edge strip question answer data as the edge strip information answer data to be displayed, wherein the edge strip information query database includes multiple standard question tags and multiple standard edge strip question answer data, and one standard question tag corresponds to one standard edge strip question answer data; acquire the edge strip information query history record of the current query subject before the query interface triggering time point, and filter out the edge strip information query history record matching the current subject interest tag from the edge strip information query history record Query and answer data, and display the edge strip historical query and answer data and the edge strip information answer data to be displayed on the edge strip information query interface; obtain the current edge strip query information made by the current query subject after reading the edge strip historical query and answer data and the edge strip information answer data to be displayed, and judge whether the current edge strip query information is consistent with the preset edge strip information display correct reply according to the current edge strip query information; if it is judged that the current edge strip query information is not consistent with the preset edge strip information display correct reply, then generate an automatic conversion to manual information query instruction, and at the same time obtain the information query keywords in the current edge strip query information, and generate and retrieve edge strip query answer data matching the information query keywords according to the information query keywords, the automatic conversion to manual information query instruction is used to control the edge strip query manual assistant to answer the current edge strip query information, and the edge strip query answer data is used to be displayed on the working interface of the edge strip query manual assistant for reference by the edge strip query manual assistant.

[0009] Specifically, the edge strip information inquiry history of the current inquiry subject before the inquiry interface is triggered is obtained, and the edge strip historical inquiry answer data matching the tag of interest to the current subject is filtered out from the edge strip information inquiry history, and the edge strip historical inquiry answer data and the edge strip information answer data to be displayed are displayed on the edge strip information inquiry interface; the previous step also includes:

[0010] Pre-acquire the edge banding purchase and sales record data of the current inquiry subject within a preset specific time period; filter out edge banding purchase process inquiry data from the edge banding purchase and sales record data according to the edge banding purchase and sales record data; perform cluster analysis on the edge banding purchase process inquiry data according to the edge banding purchase process inquiry data, and generate multiple inquiry data cluster sets, each of the inquiry data cluster sets includes multiple edge banding historical inquiry answer data; perform feature analysis on the inquiry data cluster sets, and respectively generate answer data standard labels matching the inquiry data cluster sets; establish an association relationship between the answer data standard label and the corresponding inquiry data cluster set, so that when the current subject's interested label matches the answer data standard label, the edge banding historical inquiry answer data corresponding to the answer data standard label matching the current subject's interested label is immediately filtered and called out.

[0011] Specifically, if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic-to-manual information inquiry instruction is generated, and at the same time, the information inquiry keywords in the current edge strip inquiry information are obtained, and edge strip inquiry answer data matching the information inquiry keywords are generated according to the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant, and then it also includes:

[0012] When the edge strip inquiry manual assistant answers the current edge strip inquiry information and gives the current actual solution, the feedback data of the answer given by the current inquiry subject to the current actual solution is obtained; when the answer feedback data is used to determine whether the answer feedback data completely answers the current edge strip inquiry information; if it is determined that the answer feedback data does not completely answer the current edge strip inquiry information, a preset edge strip inquiry answer database is obtained; advanced answer data matching the current edge strip inquiry information is screened out from the edge strip inquiry answer database; when the advanced answer data completely answers the current edge strip inquiry information, a classification sample is generated according to the current edge strip inquiry information and the corresponding advanced answer data; the classification sample is stored in the edge strip inquiry answer database; the data in the edge strip inquiry answer database is classified by a decision tree, and a classification decision result is obtained after the classification is completed.

[0013] Specifically, the data in the edge banding inquiry and answer database is classified by a decision tree, and after the classification is completed, a classification decision result is obtained, and then the following is further included:

[0014] A first data link is generated according to the current edge strip inquiry information; a second data link is generated according to the current actual solution; a third data link is generated according to the advanced answer data that completely answers the current edge strip inquiry information; based on the first data link, the second data link and the third data link, the current edge strip inquiry information, the current actual solution and the current edge strip inquiry information are summarized and a complete edge strip question and answer sample is generated; the complete edge strip question and answer sample is input into a preset initial edge strip inquiry neural network model for training, and an enhanced edge strip inquiry neural network model is generated.

[0015] Specifically, if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic-to-manual information inquiry instruction is generated, and at the same time, the information inquiry keywords in the current edge strip inquiry information are obtained, and edge strip inquiry answer data matching the information inquiry keywords are generated according to the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant, and then it also includes:

[0016] Obtain edge strip inquiry questions and edge strip inquiry replies of the current inquiry subject within the second specific time period, and generate a current subject edge strip inquiry data set based on the edge strip inquiry questions and the edge strip inquiry replies; perform data analysis based on the current subject edge strip inquiry data set, and obtain a first edge strip reply label and a second edge strip reply label, wherein the first edge strip reply label corresponds to the edge strip inquiry question, and the second edge strip reply label corresponds to the edge strip inquiry reply; perform information entropy calculation based on the first edge strip reply label and the second edge strip reply label, and obtain a first information entropy and a second information entropy respectively, the first information entropy corresponds to the first edge strip reply label, and the second information entropy corresponds to the second edge strip reply label; sort the edge strip inquiry questions and edge strip inquiry replies according to the size of the first information entropy and the second information entropy, and generate a sorted edge strip inquiry data set; store the sorted edge strip inquiry data set in a preset blockchain module based on hash chaining.

[0017] Specifically, an intelligent edge banding information consultation and management system, the system comprising:

[0018] An information acquisition module is used to acquire in real time the query interface triggering time point when the current query subject triggers the edge strip information query interface, and to acquire the edge strip information currently actually browsed by the current query subject at the edge strip information introduction interface before the query interface triggering time point;

[0019] An information answering module is used to generate a tag of interest to the current subject according to the currently actually browsed edge strip information, and based on the tag of interest to the current subject, filter out standard edge strip question answering data corresponding to the standard question tag matching the tag of interest to the current subject from a preset edge strip information inquiry database, and record the standard edge strip question answering data as the edge strip information answering data to be displayed, wherein the edge strip information inquiry database includes a plurality of standard question tags and a plurality of standard edge strip question answering data, and one standard question tag corresponds to one standard edge strip question answering data;

[0020] A subject inquiry module, used for obtaining the edge strip information inquiry history record of the current inquiry subject before the inquiry interface is triggered, and filtering out edge strip historical inquiry answer data matching the tag of interest to the current subject from the edge strip information inquiry history record, and displaying the edge strip historical inquiry answer data and the edge strip information answer data to be displayed on the edge strip information inquiry interface;

[0021] A subject reading module, used for obtaining the current edge strip inquiry information made by the current inquiry subject after reading the edge strip historical inquiry answer data and the edge strip information answer data to be displayed, and judging whether the current edge strip inquiry information is consistent with the preset correct answer for edge strip information display according to the current edge strip inquiry information;

[0022] The manual assistant module is used to generate an automatic-to-manual information inquiry instruction if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, and at the same time obtain the information inquiry keywords in the current edge strip inquiry information, and generate and retrieve edge strip inquiry answer data matching the information inquiry keywords based on the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant.

[0023] Specifically, the system further includes an information processing module, and the information processing module is used to:

[0024] Pre-acquire the edge banding purchase and sales record data of the current inquiry subject within a preset specific time period; filter out edge banding purchase process inquiry data from the edge banding purchase and sales record data according to the edge banding purchase and sales record data; perform cluster analysis on the edge banding purchase process inquiry data according to the edge banding purchase process inquiry data, and generate multiple inquiry data cluster sets, each of the inquiry data cluster sets includes multiple edge banding historical inquiry answer data; perform feature analysis on the inquiry data cluster sets, and respectively generate answer data standard labels matching the inquiry data cluster sets; establish an association relationship between the answer data standard label and the corresponding inquiry data cluster set, so that when the current subject's interested label matches the answer data standard label, the edge banding historical inquiry answer data corresponding to the answer data standard label matching the current subject's interested label is immediately filtered and called out;

[0025] When the edge strip inquiry artificial assistant answers the current edge strip inquiry information and gives the current actual solution, obtain the feedback data of the answer given by the current inquiry subject to the current actual solution; when judging whether the answer feedback data completely answers the current edge strip inquiry information according to the answer feedback data; if it is judged that the answer feedback data does not completely answer the current edge strip inquiry information, obtain a preset edge strip inquiry answer database; filter out advanced answer data matching the current edge strip inquiry information from the edge strip inquiry answer database; when the advanced answer data completely answers the current edge strip inquiry information, generate classification samples according to the current edge strip inquiry information and the corresponding advanced answer data; store the classification samples in the edge strip inquiry answer database; perform decision tree classification on the data in the edge strip inquiry answer database, and obtain classification decision results after the classification is completed;

[0026] Specifically, the system further includes an edge strip data processing module, and the edge strip data processing module is used to:

[0027] Generate a first data link according to the current edge strip inquiry information; generate a second data link according to the current actual solution; generate a third data link according to the advanced solution data that fully answers the current edge strip inquiry information; summarize the current edge strip inquiry information, the current actual solution and the current edge strip inquiry information based on the first data link, the second data link and the third data link to generate a complete edge strip question and answer sample; input the complete edge strip question and answer sample into a preset initial edge strip inquiry neural network model for training, and generate an enhanced edge strip inquiry neural network model;

[0028] Obtain edge strip inquiry questions and edge strip inquiry replies of the current inquiry subject within the second specific time period, and generate a current subject edge strip inquiry data set based on the edge strip inquiry questions and the edge strip inquiry replies; perform data analysis based on the current subject edge strip inquiry data set, and obtain a first edge strip reply label and a second edge strip reply label, wherein the first edge strip reply label corresponds to the edge strip inquiry question, and the second edge strip reply label corresponds to the edge strip inquiry reply; perform information entropy calculation based on the first edge strip reply label and the second edge strip reply label, and obtain a first information entropy and a second information entropy respectively, the first information entropy corresponds to the first edge strip reply label, and the second information entropy corresponds to the second edge strip reply label; sort the edge strip inquiry questions and edge strip inquiry replies according to the size of the first information entropy and the second information entropy, and generate a sorted edge strip inquiry data set; store the sorted edge strip inquiry data set in a preset blockchain module based on hash chaining.

[0029] Specifically, a computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps described in the above-mentioned intelligent edge banding information consultation management method when executing the computer program.

[0030] Specifically, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned intelligent edge banding information consultation management method are implemented.

[0031] The technical effects achieved by the present invention are as follows:

[0032] The intelligent edge strip information consultation management method and system sequentially obtain the query interface triggering time point when the current inquiring subject triggers the edge strip information query interface in real time, and obtain the current actual browsing edge strip information of the current inquiring subject at the edge strip information introduction interface before the query interface triggering time point; generate a current subject interest tag according to the current actual browsing edge strip information, and filter out standard edge strip question answer data corresponding to the standard question tag matching the current subject interest tag from a preset edge strip information query database based on the current subject interest tag, and record the standard edge strip question answer data as the edge strip information answer data to be displayed, wherein the edge strip information query database includes multiple standard question tags and multiple standard edge strip information. edge strip question answer data, one standard question tag corresponds to one standard edge strip question answer data; obtaining the edge strip information inquiry history record of the current inquiry subject before the inquiry interface triggering time point, and filtering out the edge strip historical inquiry answer data matching the tag of interest to the current subject from the edge strip information inquiry history record, and displaying the edge strip historical inquiry answer data and the edge strip information answer data to be displayed on the edge strip information inquiry interface; obtaining the current edge strip inquiry information made by the current inquiry subject after reading the edge strip historical inquiry answer data and the edge strip information answer data to be displayed, and judging whether the current edge strip inquiry information is consistent with the preset correct response to the edge strip information display according to the current edge strip inquiry information;If it is determined that the current edge strip inquiry information is not consistent with the preset correct reply to the edge strip information display, an automatic conversion to manual information inquiry instruction is generated, and at the same time, the information inquiry keywords in the current edge strip inquiry information are obtained, and edge strip inquiry answer data matching the information inquiry keywords are generated according to the information inquiry keywords. The automatic conversion to manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant, that is, by obtaining the current actual browsing edge strip information of the current inquiry subject at the edge strip information introduction interface before the inquiry interface triggering time point, and then obtaining the current actual browsing edge strip information of the current inquiry subject at the edge strip information introduction interface, so as to facilitate the subsequent automatic question display. Next, in order to predict in advance the questions that the buyer is most likely to ask after the edge strip information inquiry interface is triggered, the standard edge strip question answer data corresponding to the standard question tag matching the current subject's tag of interest is screened out from the preset edge strip information inquiry database based on the current subject's tag of interest, and the standard edge strip question answer data is recorded as the edge strip information answer data to be displayed. Then, in order to make a more accurate prediction, the edge strip information inquiry history record of the current inquiry subject before the time point when the inquiry interface is triggered is obtained in this step, and the edge strip historical inquiry answer data matching the current subject's tag of interest is screened out from the edge strip information inquiry history record. Finally, when the prediction is inaccurate, manual inquiry is actively intervened, thereby achieving efficient inquiry and answering, without the buyer actively requesting manual service, and improving the answering efficiency. ; BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of a process of an intelligent edge banding information consultation management method in one embodiment;

[0034] Figure 2 It is a structural block diagram of an intelligent edge banding information consultation management system in one embodiment;

[0035] Figure 3 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0037] In one embodiment, Figure 1As shown, an intelligent edge banding information consultation management method is provided, the method comprising:

[0038] Step S100: acquiring in real time the query interface triggering time point when the current query subject triggers the edge strip information query interface, and acquiring the edge strip information currently actually browsed by the current query subject at the edge strip information introduction interface before the query interface triggering time point;

[0039] Specifically, the current inquiring subject is a purchaser who needs to purchase edge strips, and the edge strip information inquiry interface is an input interface for purchasers to make related inquiries about edge strips. By obtaining the current actual browsing edge strip information of the current inquiring subject at the edge strip information introduction interface before the inquiry interface is triggered, the current actual browsing edge strip information of the current inquiring subject at the edge strip information introduction interface is obtained to facilitate subsequent automatic question display.

[0040] Furthermore, the edge banding information introduction interface is a commodity parameter interface of the edge banding, and the edge banding information introduction interface includes multiple information introductions of the edge banding, such as size information, usage information, price information, and material information, etc. The edge banding information actually browsed currently is one of size information, usage information, price information, and material information.

[0041] Step S200: generating a current subject interest tag according to the currently actually browsed edge strip information, and filtering out standard edge strip question answer data corresponding to a standard question tag matching the current subject interest tag from a preset edge strip information query database based on the current subject interest tag, and recording the standard edge strip question answer data as edge strip information answer data to be displayed, wherein the edge strip information query database includes a plurality of standard question tags and a plurality of standard edge strip question answer data, and one standard question tag corresponds to one standard edge strip question answer data;

[0042] Specifically, the multiple information introductions of the edge strips displayed in the edge strip information introduction interface correspond to tags that characterize the characteristics thereof, such as size information having a size tag. After obtaining the edge strip information actually browsed, the corresponding tags of interest to the current subject can be generated. Then, in order to achieve the ability to predict in advance the questions that the purchaser is most likely to want to ask after the edge strip information inquiry interface is triggered, the standard edge strip question answer data corresponding to the standard question tag that matches the current subject's tag of interest is filtered out from the preset edge strip information inquiry database based on the current subject's tag of interest, and the standard edge strip question answer data is recorded as the edge strip information answer data to be displayed.

[0043] Step S300: obtaining the edge strip information inquiry history record of the current inquiry subject before the inquiry interface is triggered, and filtering out edge strip historical inquiry answer data matching the tag of interest to the current subject from the edge strip information inquiry history record, and displaying the edge strip historical inquiry answer data and the edge strip information answer data to be displayed on the edge strip information inquiry interface;

[0044] Specifically, in order to make a more accurate prediction, the edge strip information query history record of the current inquiring subject before the query interface is triggered is obtained in this step, and the edge strip historical query answer data matching the current subject's interested tags are filtered out from the edge strip information query history record.

[0045] Next, in order to realize data visualization, the historical edge banding inquiry answer data and the edge banding information answer data to be displayed are displayed on the edge banding information inquiry interface. Compared with the prior art that requires the purchaser to actively send an inquiry message first, the present invention improves the inquiry efficiency by making a prediction first, and when the prediction is accurate.

[0046] Step S400: obtaining the current edge strip inquiry information made by the current inquiry subject after reading the edge strip historical inquiry answer data and the edge strip information answer data to be displayed, and judging whether the current edge strip inquiry information is consistent with the preset correct response to the edge strip information display according to the current edge strip inquiry information;

[0047] Specifically, in order to achieve more accurate and efficient inquiry and answering, the current edge strip inquiry information is made by obtaining the current inquiry subject's reading of the edge strip historical inquiry and answer data and the edge strip information answer data to be displayed, and judging whether the current edge strip inquiry information is consistent with the preset correct response to the edge strip information display based on the current edge strip inquiry information.

[0048] Furthermore, the correct response to the edge banding information display is pre-set, such as "OK, thank you" or "OK, thank you for your answer", which means that the buyer's inquiry has been resolved and is therefore consistent.

[0049] Step S500: If it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic-to-manual information inquiry instruction is generated, and at the same time, the information inquiry keywords in the current edge strip inquiry information are obtained, and the edge strip inquiry answer data matching the information inquiry keywords are generated and retrieved according to the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant.

[0050] Specifically, if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic transfer to manual information inquiry instruction is generated, and the automatic transfer to manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to display it on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant. Therefore, by actively intervening in manual inquiries when the prediction is inaccurate, efficient inquiry and answering are achieved, without the need for the buyer to actively request manual service, thereby improving the answering efficiency.

[0051] In one embodiment, step S300: obtaining the edge strip information inquiry history of the current inquiry subject before the inquiry interface is triggered, and filtering out edge strip historical inquiry answer data matching the tag of interest to the current subject from the edge strip information inquiry history, and displaying the edge strip historical inquiry answer data and the edge strip information answer data to be displayed on the edge strip information inquiry interface; the previous step also includes:

[0052] Step S031: pre-acquire the edge banding purchase and sales record data of the current inquiry subject within a preset specific time period;

[0053] Specifically, the preset specific time period is pre-set, and in order to ensure the accuracy and referenceability of the data, the purchase and sales record data of the edge banding within the preset specific time period is obtained.

[0054] Step S032: filtering edge banding purchase process inquiry data from the edge banding purchase sales record data according to the edge banding purchase sales record data;

[0055] Specifically, the edge strip purchase and sales record data includes a variety of record data in addition to the edge strip purchase process inquiry data, such as consumption data, purchase time data, and purchase address data, etc. Therefore, it is necessary to filter out the edge strip purchase process inquiry data from the edge strip purchase and sales record data.

[0056] Step S033: performing cluster analysis on the edge banding purchase process inquiry data according to the edge banding purchase process inquiry data, and generating a plurality of inquiry data cluster sets, each of which includes a plurality of edge banding historical inquiry answer data;

[0057] Among them, cluster analysis is an exploratory analysis. In the classification process, there is no need to give a classification standard in advance. Cluster analysis can automatically classify based on sample data and generate multiple query data cluster sets after classification.

[0058] Step S034: performing feature analysis on the query data cluster sets, and generating answer data standard labels that match the query data cluster sets respectively;

[0059] Furthermore, keywords are extracted according to the questions in each of the query data cluster sets, and the same keywords are grouped together to generate standard labels for answer data.

[0060] Step S035: Establish an association relationship between the answer data standard tag and the corresponding query data cluster set, so that when the current subject's interest tag matches the answer data standard tag, the edge banding historical query answer data corresponding to the answer data standard tag matching the current subject's interest tag is instantly filtered and called out.

[0061] Specifically, by establishing an association relationship between the answer data standard label and the corresponding query data cluster set, when the current subject's interest label matches the answer data standard label, the edge banding historical query answer data corresponding to the answer data standard label that matches the current subject's interest label can be instantly filtered and retrieved, thereby improving the query efficiency.

[0062] In one embodiment, step S500: if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic-to-manual information inquiry instruction is generated, and at the same time, an information inquiry keyword in the current edge strip inquiry information is obtained, and edge strip inquiry answer data matching the information inquiry keyword is generated according to the information inquiry keyword, the automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant, and then it also includes:

[0063] Step S510: when the edge strip inquiry artificial assistant answers the current edge strip inquiry information and gives the current actual answering solution, obtaining the answering feedback data of the current inquiry subject to the current actual answering solution;

[0064] Step S520: determining whether the answer feedback data completely answers the current edge banding inquiry information according to the answer feedback data;

[0065] The answer feedback data is judged to determine whether it includes a complete answer, such as "Thank you, I understand", "Okay", and "OK, I can place an order", etc., so as to determine whether the answer feedback data completely answers the current edge banding inquiry information.

[0066] Step S530: if it is determined that the answer feedback data does not completely answer the current edge strip inquiry information, then obtaining a preset edge strip inquiry answer database;

[0067] Step S540: Filtering out advanced answer data matching the current edge strip inquiry information from the edge strip inquiry answer database;

[0068] Step S550: when the advanced answer data completely answers the current edge strip inquiry information, generating a classification sample according to the current edge strip inquiry information and the corresponding advanced answer data;

[0069] Step S560: storing the classified samples in the edge banding query and answer database;

[0070] Step S570: performing decision tree classification on the data in the edge banding inquiry and answer database, and obtaining a classification decision result after the classification is completed.

[0071] Specifically, in order to further provide an answer, the edge strip inquiry and answer database is preset, so that when it is determined that the answer feedback data does not completely answer the current edge strip inquiry information, advanced answer data matching the current edge strip inquiry information is screened out from the edge strip inquiry and answer database. Specifically, multiple advanced answer data can be obtained until the purchaser is satisfied with the answer, that is, when the advanced answer data completely answers the current edge strip inquiry information, then, a classification sample is generated according to the current edge strip inquiry information and the corresponding advanced answer data, and the classification sample is stored in the edge strip inquiry and answer database. At the same time, the data in the edge strip inquiry and answer database is classified by a decision tree, and the classification decision result is obtained after the classification is completed. The classification decision result is obtained through decision tree classification, which is convenient for subsequent data analysis and extraction.

[0072] In one embodiment, step S570: classifying the data in the edge banding inquiry and answer database through a decision tree, and obtaining a classification decision result after the classification is completed, and then further comprising:

[0073] Step S571: generating a first data link according to the current edge strip query information;

[0074] Step S572: generating a second data link according to the current actual solution;

[0075] Step S573: generating a third data link according to the advanced answer data that completely answers the current edge strip inquiry information;

[0076] Step S574: Based on the first data link, the second data link and the third data link, the current edge strip inquiry information, the current actual solution and the current edge strip inquiry information are aggregated to generate a complete edge strip question and answer sample;

[0077] Step S575: input the complete edge banding question and answer sample into a preset initial edge banding query neural network model for training, and generate an enhanced edge banding query neural network model.

[0078] Specifically, in order to maintain the correlation between data, the first data link, the second data link and the third data link are generated to aggregate the current edge strip inquiry information, the current actual solution and the current edge strip inquiry information based on the first data link, the second data link and the third data link to generate a complete edge strip question and answer sample. A complete edge strip question and answer sample is imported into the preset initial edge strip inquiry neural network model for training, and then an enhanced edge strip inquiry neural network model is generated. The enhanced edge strip inquiry neural network model is used for subsequent answer predictions to buyers when they have more inquiries, thereby further improving inquiry efficiency.

[0079] In one embodiment, step S500: if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic-to-manual information inquiry instruction is generated, and at the same time, an information inquiry keyword in the current edge strip inquiry information is obtained, and edge strip inquiry answer data matching the information inquiry keyword is generated according to the information inquiry keyword, the automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant, and then it also includes:

[0080] Step S611: obtaining edge strip inquiry questions and edge strip inquiry replies of the current inquiry subject in the second specific time period, and generating a current subject edge strip inquiry dataset according to the edge strip inquiry questions and the edge strip inquiry replies;

[0081] Step S612: performing data analysis according to the current subject edge strip inquiry data set, and obtaining a first edge strip reply tag and a second edge strip reply tag, wherein the first edge strip reply tag corresponds to the edge strip inquiry question, and the second edge strip reply tag corresponds to the edge strip inquiry reply;

[0082] Furthermore, by collecting data within the second specific time period, a current subject edge strip query data set is generated, and then data analysis is performed, such as analysis by extracting keywords. After the analysis is completed, a first edge strip response label and a second edge strip response label are generated.

[0083] Step S613: performing information entropy calculation according to the first edge strip reply label and the second edge strip reply label, and obtaining first information entropy and second information entropy respectively, wherein the first information entropy corresponds to the first edge strip reply label, and the second information entropy corresponds to the second edge strip reply label;

[0084] Step S614: sorting the edge strip inquiry questions and edge strip inquiry replies according to the magnitudes of the first information entropy and the second information entropy, and generating a sorted edge strip inquiry data set;

[0085] Step S615: The sorted edge banding query data set is stored in a preset blockchain module based on hash chain.

[0086] Specifically, in order to sort, classify and store information, information entropy calculation is performed based on the first edge strip reply label and the second edge strip reply label, and then the edge strip inquiry questions and edge strip inquiry replies are sorted according to the size of the first information entropy and the second information entropy, and a sorted edge strip inquiry data set is generated. In order to realize data storage and tamper-proof storage, the sorted edge strip inquiry data set is stored in a preset blockchain module based on hash chain.

[0087] Further, the technical personnel in this field perform information entropy calculations by themselves to obtain the first information entropy and the second information entropy. It should be understood that the higher the entropy value of the information entropy, the greater the uncertainty of the event. When the uncertainty of the information is greater, the value of the information is higher. Therefore, the information is sorted based on its value, that is, the edge strip inquiry questions and edge strip inquiry replies are sorted according to the size of the first information entropy and the second information entropy, and a sorted edge strip inquiry data set is generated.

[0088] In one embodiment, Figure 2 As shown, an intelligent edge banding information consultation and management system is provided, the system comprising:

[0089] An information acquisition module is used to acquire in real time the query interface triggering time point when the current query subject triggers the edge strip information query interface, and to acquire the edge strip information currently actually browsed by the current query subject at the edge strip information introduction interface before the query interface triggering time point;

[0090] An information answering module is used to generate a tag of interest to the current subject according to the currently actually browsed edge strip information, and based on the tag of interest to the current subject, filter out standard edge strip question answering data corresponding to the standard question tag matching the tag of interest to the current subject from a preset edge strip information inquiry database, and record the standard edge strip question answering data as the edge strip information answering data to be displayed, wherein the edge strip information inquiry database includes a plurality of standard question tags and a plurality of standard edge strip question answering data, and one standard question tag corresponds to one standard edge strip question answering data;

[0091] A subject inquiry module, used for obtaining the edge strip information inquiry history record of the current inquiry subject before the inquiry interface is triggered, and filtering out edge strip historical inquiry answer data matching the tag of interest to the current subject from the edge strip information inquiry history record, and displaying the edge strip historical inquiry answer data and the edge strip information answer data to be displayed on the edge strip information inquiry interface;

[0092] A subject reading module, used for obtaining the current edge strip inquiry information made by the current inquiry subject after reading the edge strip historical inquiry answer data and the edge strip information answer data to be displayed, and judging whether the current edge strip inquiry information is consistent with the preset correct answer for edge strip information display according to the current edge strip inquiry information;

[0093] The manual assistant module is used to generate an automatic-to-manual information inquiry instruction if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, and at the same time obtain the information inquiry keywords in the current edge strip inquiry information, and generate and retrieve edge strip inquiry answer data matching the information inquiry keywords based on the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant.

[0094] In one embodiment, the system further comprises an information processing module, wherein the information processing module is configured to:

[0095] Pre-acquire the edge banding purchase and sales record data of the current inquiry subject within a preset specific time period; filter out edge banding purchase process inquiry data from the edge banding purchase and sales record data according to the edge banding purchase and sales record data; perform cluster analysis on the edge banding purchase process inquiry data according to the edge banding purchase process inquiry data, and generate multiple inquiry data cluster sets, each of the inquiry data cluster sets includes multiple edge banding historical inquiry answer data; perform feature analysis on the inquiry data cluster sets, and respectively generate answer data standard labels matching the inquiry data cluster sets; establish an association relationship between the answer data standard label and the corresponding inquiry data cluster set, so that when the current subject's interested label matches the answer data standard label, the edge banding historical inquiry answer data corresponding to the answer data standard label matching the current subject's interested label is immediately filtered and called out;

[0096] When the edge strip inquiry artificial assistant answers the current edge strip inquiry information and gives the current actual solution, obtain the feedback data of the answer given by the current inquiry subject to the current actual solution; when judging whether the answer feedback data completely answers the current edge strip inquiry information according to the answer feedback data; if it is judged that the answer feedback data does not completely answer the current edge strip inquiry information, obtain a preset edge strip inquiry answer database; filter out advanced answer data matching the current edge strip inquiry information from the edge strip inquiry answer database; when the advanced answer data completely answers the current edge strip inquiry information, generate classification samples according to the current edge strip inquiry information and the corresponding advanced answer data; store the classification samples in the edge strip inquiry answer database; perform decision tree classification on the data in the edge strip inquiry answer database, and obtain classification decision results after the classification is completed;

[0097] In one embodiment, the system further comprises an edge strip data processing module, wherein the edge strip data processing module is configured to:

[0098] Generate a first data link according to the current edge strip inquiry information; generate a second data link according to the current actual solution; generate a third data link according to the advanced solution data that fully answers the current edge strip inquiry information; summarize the current edge strip inquiry information, the current actual solution and the current edge strip inquiry information based on the first data link, the second data link and the third data link to generate a complete edge strip question and answer sample; input the complete edge strip question and answer sample into a preset initial edge strip inquiry neural network model for training, and generate an enhanced edge strip inquiry neural network model;

[0099] Obtain edge strip inquiry questions and edge strip inquiry replies of the current inquiry subject within the second specific time period, and generate a current subject edge strip inquiry data set based on the edge strip inquiry questions and the edge strip inquiry replies; perform data analysis based on the current subject edge strip inquiry data set, and obtain a first edge strip reply label and a second edge strip reply label, wherein the first edge strip reply label corresponds to the edge strip inquiry question, and the second edge strip reply label corresponds to the edge strip inquiry reply; perform information entropy calculation based on the first edge strip reply label and the second edge strip reply label, and obtain a first information entropy and a second information entropy respectively, the first information entropy corresponds to the first edge strip reply label, and the second information entropy corresponds to the second edge strip reply label; sort the edge strip inquiry questions and edge strip inquiry replies according to the size of the first information entropy and the second information entropy, and generate a sorted edge strip inquiry data set; store the sorted edge strip inquiry data set in a preset blockchain module based on hash chaining.

[0100] In one embodiment, Figure 3 As shown, a computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps described in the above-mentioned intelligent edge banding information consultation management method when executing the computer program.

[0101] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned intelligent edge banding information consultation management method.

[0102] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database 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. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0103] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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.

[0104] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. An intelligent edge banding information consultation management method, characterized in that: The method comprises: Acquire in real time the query interface triggering time point when the current query subject triggers the edge strip information query interface, and acquire the current actual browsing edge strip information of the current query subject at the edge strip information introduction interface before the query interface triggering time point; generate a current subject interest tag according to the current actual browsing edge strip information, and filter out standard edge strip question answer data corresponding to the standard question tag matching the current subject interest tag from a preset edge strip information query database based on the current subject interest tag, and record the standard edge strip question answer data as the edge strip information answer data to be displayed, wherein the edge strip information query database includes multiple standard question tags and multiple standard edge strip question answer data, and one standard question tag corresponds to one standard edge strip question answer data; acquire the edge strip information query history record of the current query subject before the query interface triggering time point, and filter out the edge strip information query history record matching the current subject interest tag from the edge strip information query history record Query and answer data, and display the edge strip historical query and answer data and the edge strip information answer data to be displayed on the edge strip information query interface; obtain the current edge strip query information made by the current query subject after reading the edge strip historical query and answer data and the edge strip information answer data to be displayed, and judge whether the current edge strip query information is consistent with the preset edge strip information display correct reply according to the current edge strip query information; if it is judged that the current edge strip query information is not consistent with the preset edge strip information display correct reply, then generate an automatic conversion to manual information query instruction, and at the same time obtain the information query keywords in the current edge strip query information, and generate and retrieve edge strip query answer data matching the information query keywords according to the information query keywords, the automatic conversion to manual information query instruction is used to control the edge strip query manual assistant to answer the current edge strip query information, and the edge strip query answer data is used to be displayed on the working interface of the edge strip query manual assistant for reference by the edge strip query manual assistant.

2. The intelligent edge banding information consultation and management method according to claim 1 is characterized in that: Acquire the edge strip information inquiry history of the current inquiry subject before the inquiry interface triggering time point, and filter out edge strip historical inquiry answer data matching the tag of interest to the current subject from the edge strip information inquiry history, and display the edge strip historical inquiry answer data and the edge strip information answer data to be displayed on the edge strip information inquiry interface; the previous also includes: Pre-acquire the edge banding purchase and sales record data of the current inquiry subject within a preset specific time period; filter out edge banding purchase process inquiry data from the edge banding purchase and sales record data according to the edge banding purchase and sales record data; perform cluster analysis on the edge banding purchase process inquiry data according to the edge banding purchase process inquiry data, and generate multiple inquiry data cluster sets, each of the inquiry data cluster sets includes multiple edge banding historical inquiry answer data; perform feature analysis on the inquiry data cluster sets, and respectively generate answer data standard labels matching the inquiry data cluster sets; establish an association relationship between the answer data standard label and the corresponding inquiry data cluster set, so that when the current subject's interested label matches the answer data standard label, the edge banding historical inquiry answer data corresponding to the answer data standard label matching the current subject's interested label is immediately filtered and called out.

3. The intelligent edge banding information consultation and management method according to claim 1 is characterized in that: If it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic-to-manual information inquiry instruction is generated, and at the same time, the information inquiry keywords in the current edge strip inquiry information are obtained, and edge strip inquiry answer data matching the information inquiry keywords are generated according to the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant, and then it also includes: When the edge strip inquiry manual assistant answers the current edge strip inquiry information and gives the current actual solution, the feedback data of the answer given by the current inquiry subject to the current actual solution is obtained; when the answer feedback data is used to determine whether the answer feedback data completely answers the current edge strip inquiry information; if it is determined that the answer feedback data does not completely answer the current edge strip inquiry information, a preset edge strip inquiry answer database is obtained; advanced answer data matching the current edge strip inquiry information is screened out from the edge strip inquiry answer database; when the advanced answer data completely answers the current edge strip inquiry information, a classification sample is generated according to the current edge strip inquiry information and the corresponding advanced answer data; the classification sample is stored in the edge strip inquiry answer database; the data in the edge strip inquiry answer database is classified by a decision tree, and a classification decision result is obtained after the classification is completed.

4. The intelligent edge banding information consultation and management method according to claim 3 is characterized in that: The data in the edge banding inquiry and answer database are classified by a decision tree, and after the classification is completed, a classification decision result is obtained, and then the following is further included: A first data link is generated according to the current edge strip inquiry information; a second data link is generated according to the current actual solution; a third data link is generated according to the advanced answer data that completely answers the current edge strip inquiry information; based on the first data link, the second data link and the third data link, the current edge strip inquiry information, the current actual solution and the current edge strip inquiry information are summarized and a complete edge strip question and answer sample is generated; the complete edge strip question and answer sample is input into a preset initial edge strip inquiry neural network model for training, and an enhanced edge strip inquiry neural network model is generated.

5. The intelligent edge banding information consultation and management method according to any one of claims 1 to 4, characterized in that: If it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, an automatic-to-manual information inquiry instruction is generated, and at the same time, the information inquiry keywords in the current edge strip inquiry information are obtained, and edge strip inquiry answer data matching the information inquiry keywords are generated according to the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant, and then it also includes: Obtain edge strip inquiry questions and edge strip inquiry replies of the current inquiry subject within the second specific time period, and generate a current subject edge strip inquiry data set based on the edge strip inquiry questions and the edge strip inquiry replies; perform data analysis based on the current subject edge strip inquiry data set, and obtain a first edge strip reply label and a second edge strip reply label, wherein the first edge strip reply label corresponds to the edge strip inquiry question, and the second edge strip reply label corresponds to the edge strip inquiry reply; perform information entropy calculation based on the first edge strip reply label and the second edge strip reply label, and obtain a first information entropy and a second information entropy respectively, the first information entropy corresponds to the first edge strip reply label, and the second information entropy corresponds to the second edge strip reply label; sort the edge strip inquiry questions and edge strip inquiry replies according to the size of the first information entropy and the second information entropy, and generate a sorted edge strip inquiry data set; store the sorted edge strip inquiry data set in a preset blockchain module based on hash chaining.

6. An intelligent edge banding information consultation and management system, characterized in that: The system comprises: An information acquisition module is used to acquire in real time the query interface triggering time point when the current query subject triggers the edge strip information query interface, and to acquire the edge strip information currently actually browsed by the current query subject at the edge strip information introduction interface before the query interface triggering time point; An information answering module is used to generate a tag of interest to the current subject according to the currently actually browsed edge strip information, and based on the tag of interest to the current subject, filter out standard edge strip question answering data corresponding to the standard question tag matching the tag of interest to the current subject from a preset edge strip information inquiry database, and record the standard edge strip question answering data as the edge strip information answering data to be displayed, wherein the edge strip information inquiry database includes a plurality of standard question tags and a plurality of standard edge strip question answering data, and one standard question tag corresponds to one standard edge strip question answering data; A subject inquiry module, used for obtaining the edge strip information inquiry history record of the current inquiry subject before the inquiry interface is triggered, and filtering out edge strip historical inquiry answer data matching the tag of interest to the current subject from the edge strip information inquiry history record, and displaying the edge strip historical inquiry answer data and the edge strip information answer data to be displayed on the edge strip information inquiry interface; A subject reading module, used for obtaining the current edge strip inquiry information made by the current inquiry subject after reading the edge strip historical inquiry answer data and the edge strip information answer data to be displayed, and judging whether the current edge strip inquiry information is consistent with the preset correct answer for edge strip information display according to the current edge strip inquiry information; The manual assistant module is used to generate an automatic-to-manual information inquiry instruction if it is determined that the current edge strip inquiry information is not consistent with the preset correct response to the edge strip information display, and at the same time obtain the information inquiry keywords in the current edge strip inquiry information, and generate and retrieve edge strip inquiry answer data matching the information inquiry keywords based on the information inquiry keywords. The automatic-to-manual information inquiry instruction is used to control the edge strip inquiry manual assistant to answer the current edge strip inquiry information, and the edge strip inquiry answer data is used to be displayed on the working interface of the edge strip inquiry manual assistant for reference by the edge strip inquiry manual assistant.

7. The intelligent edge banding information consultation and management system according to claim 6 is characterized in that: The system further comprises an information processing module, wherein the information processing module is used for: Pre-acquire the edge banding purchase and sales record data of the current inquiry subject within a preset specific time period; filter out edge banding purchase process inquiry data from the edge banding purchase and sales record data according to the edge banding purchase and sales record data; perform cluster analysis on the edge banding purchase process inquiry data according to the edge banding purchase process inquiry data, and generate multiple inquiry data cluster sets, each of which includes multiple edge banding historical inquiry answer data; perform feature analysis on the inquiry data cluster sets, and respectively generate answer data standard labels that match the inquiry data cluster sets; Establishing an association relationship between the answer data standard tag and the corresponding query data cluster set, so that when the current subject's interest tag matches the answer data standard tag, the edge banding historical query answer data corresponding to the answer data standard tag matching the current subject's interest tag is instantly screened and retrieved; When the edge strip inquiry manual assistant answers the current edge strip inquiry information and gives the current actual solution, obtain the feedback data of the answer given by the current inquiry subject to the current actual solution; when judging whether the answer feedback data completely answers the current edge strip inquiry information according to the answer feedback data; if it is judged that the answer feedback data does not completely answer the current edge strip inquiry information, obtain a preset edge strip inquiry answer database; filter out advanced answer data matching the current edge strip inquiry information from the edge strip inquiry answer database; when the advanced answer data completely answers the current edge strip inquiry information, generate classification samples according to the current edge strip inquiry information and the corresponding advanced answer data; The classified samples are stored in the edge banding inquiry and answer database; the data in the edge banding inquiry and answer database are classified by a decision tree, and a classification decision result is obtained after the classification is completed.

8. The intelligent edge banding information consultation and management system according to claim 6 is characterized in that: The system further comprises an edge banding data processing module, wherein the edge banding data processing module is used for: Generate a first data link according to the current edge strip inquiry information; generate a second data link according to the current actual solution; generate a third data link according to the advanced solution data that fully solves the current edge strip inquiry information; Based on the first data link, the second data link and the third data link, the current edge strip inquiry information, the current actual solution and the current edge strip inquiry information are summarized and a complete edge strip question and answer sample is generated; the complete edge strip question and answer sample is input into a preset initial edge strip inquiry neural network model for training, and an enhanced edge strip inquiry neural network model is generated; Obtain edge strip inquiry questions and edge strip inquiry replies of the current inquiry subject within the second specific time period, and generate a current subject edge strip inquiry data set based on the edge strip inquiry questions and the edge strip inquiry replies; perform data analysis based on the current subject edge strip inquiry data set, and obtain a first edge strip reply label and a second edge strip reply label, wherein the first edge strip reply label corresponds to the edge strip inquiry question, and the second edge strip reply label corresponds to the edge strip inquiry reply; perform information entropy calculation based on the first edge strip reply label and the second edge strip reply label, and obtain a first information entropy and a second information entropy respectively, the first information entropy corresponds to the first edge strip reply label, and the second information entropy corresponds to the second edge strip reply label; sort the edge strip inquiry questions and edge strip inquiry replies according to the size of the first information entropy and the second information entropy, and generate a sorted edge strip inquiry data set; store the sorted edge strip inquiry data set in a preset blockchain module based on hash chaining.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

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

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