An electronic business card intelligent generation system and method based on artificial intelligence

Abstract

The application discloses an electronic business card intelligent generation system and method based on artificial intelligence, and relates to the technical field of artificial intelligence, and comprises the following steps: obtaining the content editing part of each electronic business card template, determining each use user and individual information, and obtaining the keyword set corresponding to each electronic business card template; obtaining the evaluation test result of a current target user, extracting a target word, and obtaining the preference coefficient of the target user and each electronic business card template; obtaining a recommended template according to the preference coefficient; if the target user becomes a use user of the recommended template, updating the keyword set corresponding to the recommended template; if the target user does not become a use user, reacquiring the preference coefficient until the target user determines a suitable electronic business card template. The application analyzes the individual information of the use user, recommends a suitable electronic business card template for the target user, performs multi-dimensional data comprehensive analysis, and more accurately recommends an electronic business card template suitable for the individuality of the user.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, and particularly relates to an electronic business card intelligent generation system and method based on artificial intelligence. BACKGROUND

[0002] An electronic business card is a digital form of a business card, usually containing basic information of an individual or a company, such as name, position, company name, contact information, address, etc. It can be shared and spread through email, social media, QR code, etc. It has the advantages of convenience, environmental protection and personalization. However, there are many types of electronic business cards at present, and when recommending suitable electronic business card templates to users, a single recommendation according to occupation or industry is often used, without fully considering the individual factors of users, such as occupation characteristics and style preferences, resulting in the inability to intelligently recommend according to the individuality of people. Therefore, according to the historical selection records of each template, combined with multi-dimensional data such as user personality data and preferences, comprehensive analysis can be carried out to more accurately recommend electronic business card templates suitable for the individuality of users and meet the unique needs and changes of different users. SUMMARY

[0003] The present application aims to provide an electronic business card intelligent generation system and method based on artificial intelligence to solve the problems in the prior art.

[0004] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0005] An electronic business card intelligent generation method based on artificial intelligence, comprising the following steps:

[0006] Step S100: Obtain the content editing part on each electronic business card template, determine the use user corresponding to the electronic business card template and the individual information of the use user according to the content change of the content editing part, and perform evaluation test on each user on the electronic business card platform, extract keywords from the evaluation test content and the individual information according to the evaluation test result, and analyze to obtain a keyword set corresponding to each electronic business card template;

[0007] Step S200: According to the evaluation test result of the current target user, extract the target word, and according to each keyword in the keyword set, obtain the weight vector corresponding to the electronic business card template; according to the similarity between the target word and each keyword, obtain the word vector of the electronic business card template, and according to the weight vector and the word vector, obtain the preference coefficient of the target user and each electronic business card template;

[0008] Step S300: Obtain the recommended template according to the preference coefficient, recommend the recommended template to the target user, and if the target user becomes the use user of the recommended template, update the keyword set corresponding to the recommended template;

[0009] Step S400: if the target user is not a user of the recommended template, prompting the target user to input the influencing factor content, and analyzing the input content, reacquiring the preference coefficient of the target user and each electronic business card template, and so on until the target user determines the appropriate electronic business card template.

[0010] Further, step S100 includes:

[0011] Step S110: obtaining all electronic business card templates in the electronic business card platform, and obtaining all content editing parts on each electronic business card template; if a user edits based on a certain electronic business card template, and all content editing parts on the certain electronic business card template are modified, the user is regarded as a user of the certain electronic business card template, the modified content editing parts are regarded as the personal information of the user, and all users corresponding to each electronic business card template are obtained.

[0012] In the present scheme, the content editing parts include name, position, position keyword, unit, telephone, address information and self-introduction. The position keyword is determined according to the position, for example, if the position is designer, the personal keyword is any one or more of the labels such as unlimited creativity, color master, simple fashion, efficient output, strong stress resistance, etc.; if the position is salesperson, the personal keyword is any one or more of the labels such as communication expert, customer demand grasping, outstanding adaptability, strong stress resistance, etc. The specific keyword label should be determined according to the actual situation, but should highlight the professional characteristics of the individual.

[0013] Step S120: judging and testing each user on the electronic business card platform, the content of the judging and testing including selecting the occupation and scoring the professional keyword, and selecting the design elements of the electronic business card template, the design elements including color, style and layout; obtaining the judging and testing results of each user, if the judging and testing time of a certain user is greater than the time threshold, and the scores of the professional keywords are not the highest or the lowest, the certain user is regarded as an effective user; if a certain user of a certain electronic business card template is an effective user, obtaining all personal keywords in the personal information corresponding to the certain user.

[0014] In the present embodiment, the professional keyword should match the occupation, the design elements include color, style and layout, the color is the theme color of the electronic business card template, the style is the atmosphere and characteristics of the electronic business card template, including retro, cool, government affairs, business and fashion, etc., and the layout is the overall layout and visual style of the electronic business card template, including horizontal graph, vertical graph and square graph, etc.

[0015] Step S130: setting the weight value of each personality keyword as 1, obtaining the similarity of each personality keyword and each professional keyword, normalizing, and taking the maximum similarity of a certain personality keyword as X, and the score of the professional keyword corresponding to the maximum similarity X as Y, and then obtaining the maximum weight value W of a certain personality keyword = 1 + [Y * (X-0.5) / K], wherein X ∈ [0, 1], K is a weight coefficient, and K > 0; adding the weight values of the same personality keywords in each user corresponding to a certain electronic business card template, sorting the personality keywords in turn according to the total weight value from large to small, and establishing a keyword set.

[0016] The similarity represents the similarity between the actual input of a certain keyword by the user and the professional keyword of the test. When the maximum similarity X is greater than 0.5, it means that the professional keyword of the test is highly matched with the actual input of a certain keyword by the user, that is, when X-0.5 > 0, the score of the test at this time has a positive meaning for evaluating the electronic business card template, so the maximum weight value W at this time is greater than 1. When the score Y of the professional keyword of the test is larger, it means that the user with the keyword is more inclined to select the electronic business card template, and when the score Y of the test is smaller, it means that the user with the certain keyword is not inclined to select the electronic business card template.

[0017] Further, step S200 includes:

[0018] Step S210: obtaining the evaluation test result of the target user, taking the selected design elements in the evaluation test result and the professional keywords with a score greater than a score threshold as target keywords; obtaining the design elements of all electronic business card templates, taking an electronic business card template as a predetermined template if the design elements of the electronic business card template contain at least one of the design elements corresponding to the target keywords; obtaining the keyword set corresponding to a certain predetermined template, and extracting the personality keywords with a sequence number less than a sequence number threshold in the keyword set as predetermined keywords;

[0019] Step S220: adding the maximum weight values corresponding to each predetermined keyword to obtain a total weight value, dividing each maximum weight value by the total weight value to obtain a weight ratio corresponding to each predetermined keyword, and then obtaining a weight vector corresponding to a certain predetermined template;

[0020] Step S230: obtaining the similarity of each predetermined keyword of a certain predetermined template and each professional keyword in the target keywords, normalizing, taking the maximum similarity corresponding to each predetermined keyword as the word weight corresponding to each predetermined keyword, and then obtaining the word vector of a certain predetermined template, multiplying the weight vector by the word vector to obtain the preference coefficient of the target user and a certain predetermined template, and then obtaining the preference coefficient of the target user and each predetermined template.

[0021] The weight vector represents the weight of each predetermined keyword corresponding to the electronic business card template by the user, and the higher the weight, the more the corresponding keyword can be used to represent the electronic business card template.

[0022] Further, the step S300 comprises:

[0023] Step S310: The electronic business card template corresponding to the maximum preference coefficient is taken as the recommended template, and the recommended template is recommended to the target user. If the target user becomes the user of the recommended template within the time range T after the recommendation, all information keywords in the information content corresponding to the modified content editing part are obtained.

[0024] Step S320: The number N of information keywords corresponding to the target user that are the same as the target keyword is obtained, and the credibility F of the target user is obtained as F=1-e -H*N , where e is the natural index, and H is the preset credibility coefficient; according to the credibility F, the weight of each predetermined keyword in the recommended template is changed, the changed weight is W0+(1+F*M), where W0 is the initial weight of a certain predetermined keyword, M is the word weight corresponding to a certain predetermined keyword, and the predetermined keywords are reordered according to the changed weight from large to small, and then the keyword set corresponding to the recommended template is updated.

[0025] Further, the step S400 comprises:

[0026] Step S410: If the target user does not edit based on the recommended template within the time range T after the recommendation, or edits based on the recommended template but not all information contents corresponding to the content editing part are modified, it is judged that the target user is not the user of the recommended template, and the target user is prompted to input the reason S p for not using, and the target preference S q is obtained, and the weight of the resisting target keyword is set as W p , the weight of the preferred target keyword is set as W q , W p <0< W r <1< W q , where W r is the feature weight.

[0027] Step S420: All individual keywords with a serial number less than the serial number threshold in the keyword set corresponding to a certain electronic business card template are obtained, and the maximum weight of each individual keyword is obtained, the number of individual keywords is taken as T, and the preference coefficient of the certain electronic business card template is obtained. , where A is the number of keywords in the reason S p for not using that are the same as the individual keywords, W a is the maximum weight of the a-th individual keyword, and D is the target preference Sq W is the number of keywords in the keyword set corresponding to the dth personality keyword, A is the number of feature keywords, B is the number of personality keywords, and B = T - A - D, W d B is the maximum weight value corresponding to the bth personality keyword; and the preference coefficient of the target user and each electronic business card template is obtained. b B is the maximum weight value corresponding to the bth personality keyword; and the preference coefficient of the target user and each electronic business card template is obtained.

[0028] An electronic business card intelligent generation system based on artificial intelligence, comprising a keyword set obtaining module, a preference coefficient calculation module, a keyword set updating module, and a determination of an electronic business card template module.

[0029] The keyword set obtaining module is used to obtain the content editing part on each electronic business card template, determine the corresponding user of the electronic business card template and the personality information of the user according to the content change of the content editing part, and perform a judgment test on each user on the electronic business card platform, extract keywords from the judgment test content and the personality information according to the judgment test result, and analyze to obtain the keyword set corresponding to each electronic business card template.

[0030] The preference coefficient calculation module is used to extract target words according to the judgment test result of the current target user, obtain the weight vector corresponding to the electronic business card template according to each keyword in the keyword set, obtain the word vector of the electronic business card template according to the similarity between the target words and each keyword, and obtain the preference coefficient of the target user and each electronic business card template according to the weight vector and the word vector.

[0031] The keyword set updating module is used to obtain the recommended template according to the preference coefficient, recommend the recommended template to the target user, and update the keyword set corresponding to the recommended template if the target user becomes the user of the recommended template.

[0032] The determination of an electronic business card template module is used to prompt the target user to input the influencing factor content and analyze the input content if the target user is not the user of the recommended template, reobtain the preference coefficient of the target user and each electronic business card template, and so on until the target user determines the appropriate electronic business card template.

[0033] Further, the keyword set obtaining module comprises a user obtaining unit, a personality keyword obtaining unit, and a keyword set obtaining unit.

[0034] The user obtaining unit is used to obtain all electronic business card templates in the electronic business card platform, obtain the corresponding user of each electronic business card template, and obtain the personality information of each user.

[0035] Obtaining personality keyword unit: used for judging test on each user on the electronic business card platform, and then obtaining an effective user; if a certain use user corresponding to a certain electronic business card template is an effective user, obtaining all personality keywords in the personality information corresponding to the certain use user;

[0036] Obtaining keyword set unit: used for setting the weight of each personality keyword, obtaining the similarity between each personality keyword and each professional keyword, and obtaining the maximum weight of a certain personality keyword.

[0037] Further, the keyword set updating module includes an obtaining recommendation template unit and a keyword set updating unit;

[0038] Obtaining recommendation template unit: used for taking the electronic business card template corresponding to the maximum preference coefficient as a recommendation template, recommending the recommendation template to a target user, and if the target user becomes a use user of the recommendation template within a time range T after the recommendation, obtaining all information keywords in the information content corresponding to the modified content editing part;

[0039] Keyword set updating unit: used for obtaining the number of information keywords corresponding to the target user that are the same as the target word, obtaining the credibility of the target user; changing the weight of each predetermined keyword in the recommendation template, and reordering according to the weight of each predetermined keyword in descending order, and then updating the keyword set corresponding to the recommendation template.

[0040] Compared with the prior art, the beneficial effects of the present application are: the present application provides an electronic business card intelligent generation system and method based on artificial intelligence, which comprises: obtaining the content editing part of each electronic business card template, determining each use user and personality information, and obtaining the keyword set corresponding to each electronic business card template; obtaining the judgment test result of the current target user, extracting the target word, and obtaining the preference coefficient of the target user and each electronic business card template; obtaining the recommendation template according to the preference coefficient, if the target user becomes a use user of the recommendation template, updating the keyword set corresponding to the recommendation template; if not, re-obtaining the preference coefficient until the target user determines a suitable electronic business card template. The present application analyzes the personality information of the use user, recommends a suitable electronic business card template for the target user, and comprehensively analyzes the multi-dimensional data such as the personality data and preferences of the user, more accurately recommends an electronic business card template suitable for the personality of the user, and meets the unique needs and changes of different users. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 The flowchart of the present application is a kind of intelligent generation method based on artificial intelligence of electronic business card;

[0042] Figure 2The structural diagram of the electronic business card intelligent generation system based on artificial intelligence. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0044] Embodiment: As shown in the figure, the present application provides an electronic business card intelligent generation system and method based on artificial intelligence, which comprises the following steps: Figure 1

[0045] Step S100: Obtain the content editing part on each electronic business card template, determine the use user corresponding to the electronic business card template and the individual information of the use user according to the content change of the content editing part; judge and test each user on the electronic business card platform, extract keywords from the judgment test content and individual information according to the judgment test result, and analyze to obtain the keyword set corresponding to each electronic business card template.

[0046] Step S110: Obtain all electronic business card templates in the electronic business card platform, and obtain all content editing parts on each electronic business card template; if a user edits based on a certain electronic business card template, and the information content corresponding to all content editing parts on the certain electronic business card template is modified, the user is taken as the use user of the certain electronic business card template, the modified information content corresponding to the content editing part is taken as the individual information of the use user, and all use users corresponding to each electronic business card template are obtained.

[0047] In the present scheme, the content editing part includes name, position, position keyword, unit, telephone, address information and self-introduction. The position keyword is determined according to the position, for example, if the position is designer, the personal keyword is any one or more of the labels such as unlimited creativity, color master, simple fashion, efficient output, strong stress resistance, etc.; if the position is sales personnel, the personal keyword is any one or more of the labels such as communication expert, customer demand grasping, outstanding adaptability, strong stress resistance, etc. The specific keyword label should be determined according to the actual situation, but the professional characteristics of the individual should be highlighted.

[0048] ​Step S120: a judgment test is conducted on each user on the electronic business card platform, the content of the judgment test includes selecting the occupation and scoring the key words of each occupation, and selecting the design elements of the electronic business card template, the design elements include color, style and layout; the judgment test results of each user are obtained, if the judgment test time of a certain user is greater than the time threshold, and the scores of the key words of each occupation are not the highest or the lowest, the certain user is regarded as an effective user; if a certain use user corresponding to a certain electronic business card template is an effective user, all the personal key words in the personal information corresponding to the certain use user are obtained.

[0049] In the embodiment, the occupation key words should match the occupation, the design elements include color, style and layout, wherein the color is the theme color of the electronic business card template; the style is the atmosphere and characteristics of the electronic business card template, including retro, cool, government, business and fashion; the layout is the overall layout and visual style of the electronic business card template, including horizontal graph, vertical graph and square graph.

[0050] Step S130: the weight of each personal key word is set to 1, the similarity between each personal key word and each occupation key word is obtained, and is normalized, the maximum similarity corresponding to a certain personal key word is X, when the maximum similarity X is, the score of the occupation key word corresponding to the maximum similarity X is Y, and then the maximum weight W of a certain personal key word is obtained W=1+[Y*(X-0.5) / K], wherein X∈[0,1], K is a weight coefficient, K>0; the same personal key words in each use user corresponding to a certain electronic business card template are added in weight, each personal key word is sorted in order from large to small according to the total weight, and a key word set is established.

[0051] The similarity represents the similarity between the actual input of a certain key word of the user and the occupation key word of the test, when the maximum similarity X is greater than 0.5, it means that the occupation key word of the test question is highly matched with the actual input of a certain key word of the user, that is, when X-0.5>0, the score of the test question has a positive meaning for evaluating the electronic business card template, so the maximum weight W is greater than 1 at this time, when the score Y of the occupation key word of the test question is larger, it means that the user with the key word is more inclined to select the electronic business card template, and when the score Y of the test question is smaller, it means that the user with the certain key word is not inclined to select the electronic business card template. In the embodiment, the score is ten, that is, Y∈[0,10], and the weight coefficient K=10.

[0052] Step S200: according to the evaluation test result of the current target user, extracting the target word, and obtaining the weight vector corresponding to the electronic business card template according to each keyword in the keyword set; obtaining the word vector of the electronic business card template according to the similarity between the target word and each keyword, and obtaining the preference coefficient of the target user and each electronic business card template according to the weight vector and the word vector;

[0053] Step S210: obtaining the evaluation test result of the target user, selecting the design elements in the evaluation test result, and the professional keywords with the score greater than the score threshold as the target word; obtaining the design elements of all electronic business card templates, and taking a certain electronic business card template as a predetermined template if the design elements of the certain electronic business card template contain at least one of the design elements corresponding to the target word; obtaining the keyword set corresponding to the certain predetermined template, and extracting the individual keywords in the keyword set with the serial number less than the serial number threshold as the predetermined keywords.

[0054] Step S220: adding the maximum weights corresponding to each predetermined keyword to obtain the total weight, and dividing each maximum weight by the total weight to obtain the weight ratio corresponding to each predetermined keyword, and then obtaining the weight vector corresponding to the certain predetermined template.

[0055] Step S230: obtaining the similarity between each predetermined keyword of a certain predetermined template and each professional keyword in the target word, and normalizing, taking the maximum similarity corresponding to each predetermined keyword as the word weight corresponding to each predetermined keyword, and then obtaining the word vector of the certain predetermined template, multiplying the weight vector by the word vector to obtain the preference coefficient of the target user and the certain predetermined template, and then obtaining the preference coefficient of the target user and each predetermined template.

[0056] The weight vector represents the weight of each predetermined keyword corresponding to the electronic business card template used by the user, and the higher the weight, the more the corresponding keyword can be used to represent the electronic business card template.

[0057] Step S300: obtaining the recommended template according to the preference coefficient, recommending the recommended template to the target user, and updating the keyword set corresponding to the recommended template if the target user becomes the user of the recommended template;

[0058] Step S310: taking the electronic business card template corresponding to the maximum preference coefficient as the recommended template, recommending the recommended template to the target user, and obtaining all information keywords in the information content corresponding to the modified content editing part if the target user becomes the user of the recommended template within the time range T after the recommendation;

[0059] Step S320: obtaining the number N of information keywords corresponding to the target user which are the same as the target word, and obtaining the credibility F of the target user F = 1 - e -H*NWherein, e is a natural index, H is a preset reliability coefficient; according to the reliability degree F, the weight of each predetermined keyword in the recommended template is changed, the changed weight is W0+(1+F*M), wherein W0 is the initial weight of a certain predetermined keyword, M is the word weight corresponding to a certain predetermined keyword, and each predetermined keyword is reordered according to the changed weight from large to small, and then the keyword set corresponding to the recommended template is updated.

[0060] Step S400: If the target user is not a user of the recommended template, prompting the target user to input the influence factor content, and analyzing the input content, reacquiring the preference coefficient of the target user and each electronic business card template, and so on, until the target user determines the appropriate electronic business card template.

[0061] Step S410: If the target user does not edit based on the recommended template within the recommended time range T, or edits based on the recommended template, but not all content editing parts corresponding to the information content are modified, it is judged that the target user is not a user of the recommended template, prompting the target user to input the reason S p and the target preference S q , and setting the resistance target word weight as W p , the preference target word weight as W q , W p <0<W r <1<W q , wherein W r is the feature weight;

[0062] Wherein, the influence factor content includes the reason S for not using and the target preference.

[0063] Step S420: acquiring all individual keywords with a serial number less than the serial number threshold in the keyword set corresponding to a certain electronic business card template, and the maximum weight value of each individual keyword, taking the number of individual keywords as T, and then obtaining the preference coefficient of the certain electronic business card template , wherein A is the number of keywords in the reason S p for not using which are the same as the individual keywords, W a is the maximum weight value of the corresponding a-th individual keyword, D is the number of keywords in the target preference S q which are the same as the individual keywords, W d is the maximum weight value of the corresponding d-th individual keyword, B is the number of feature keywords, B=T-A-D, W b is the maximum weight value of the corresponding b-th individual keyword; and then obtaining the preference coefficient of the target user and each electronic business card template, and so on according to the above steps S300 to S400, until the target user determines the appropriate electronic business card template.

[0064] In this embodiment, the sequence number threshold is 5, the resistance target word weight W p = -1, the feature weight W r = 0.5, the preference target word weight W q = 2.

[0065] It will be obvious to a person skilled in the art that, without departing from the scope of the application, the application can be implemented in other specific forms. The embodiments are therefore to be considered in all respects as being illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the description above, which is given solely for the purposes of explanation and is not intended to limit the application. Any reference signs in the claims should not be construed as limiting the scope of the claims.

Claims

1. An artificial intelligence-based electronic business card intelligent generation method, characterized in that, The method comprises the following steps: Step S100: obtaining the content editing part on each electronic business card template, determining the use user corresponding to the electronic business card template and the individual information of the use user according to the content change of the content editing part; Step S200: extracting the target word according to the evaluation test result of the target user, obtaining the weight vector corresponding to the electronic business card template according to each keyword in the keyword set, obtaining the word vector of the electronic business card template according to the similarity between the target word and each keyword, and obtaining the preference coefficient of the target user and each electronic business card template according to the weight vector and the word vector; Step S300: obtaining the recommended template according to the preference coefficient, recommending the recommended template to the target user, updating the keyword set corresponding to the recommended template if the target user becomes the use user of the recommended template; Step S400: if the target user is not the use user of the recommended template, prompting the target user to input the influencing factor content, analyzing the input content, re-obtaining the preference coefficient of the target user and each electronic business card template, and repeating the above steps until the target user determines the appropriate electronic business card template; Step S300 comprises: Step S310: taking the electronic business card template corresponding to the maximum preference coefficient as the recommended template, recommending the recommended template to the target user, and obtaining all information keywords in the information content corresponding to the modified content editing part if the target user becomes the use user of the recommended template within the time range T after the recommendation; Step S100 comprises: Step S320: obtaining the number N of information keywords corresponding to the target user which are same as the target word, and obtaining the trust degree F=1-e -H*N of the target user, wherein e is a natural index, and H is a preset trust coefficient; according to the trust degree F, changing the weight of each predetermined keyword in the recommendation template, the changed weight being W0+(1+F*M), wherein W0 is an initial weight of a certain predetermined keyword, and M is a word weight corresponding to the certain predetermined keyword, and reordering according to the changed weight of each predetermined keyword from large to small, and then updating the keyword set corresponding to the recommendation template. 2.The AI-based electronic business card intelligent generation method of claim 1, wherein, Step S110: obtaining all electronic business card templates in the electronic business card platform and obtaining all content editing parts on each electronic business card template; if a user edits based on a certain electronic business card template and all information contents corresponding to all content editing parts on the certain electronic business card template are modified, the user is taken as the use user of the certain electronic business card template, the information content corresponding to the modified content editing part is taken as the individual information of the use user, and all use users corresponding to each electronic business card template are obtained; Step S120: performing evaluation test on each user in the electronic business card platform, the content of the evaluation test including selecting the occupation and scoring the professional keywords, and selecting the design elements of the electronic business card template, the design elements including color, style and layout; obtaining the evaluation test result of each user, taking a user as an effective user if the evaluation test time of the user is greater than a time threshold and the scores of the professional keywords are not all the highest or the lowest; obtaining all individual keywords in the individual information of a use user corresponding to a certain electronic business card template if the use user is an effective user; ​ Step S130: setting the weight value of each personality keyword as 1, obtaining the similarity of each personality keyword and each professional keyword, normalizing, and taking the maximum similarity of a certain personality keyword as X. When the maximum similarity X is obtained, the score of the professional keyword corresponding to the maximum similarity X is Y. Then the maximum weight value W of a certain personality keyword is obtained as W=1+[Y*(X-0.5) / K], wherein X∈[0,1] and K is a weight coefficient, K>0. The weight values of the same personality keywords in each user corresponding to a certain electronic business card template are added. According to the order from large to small of the total weight value, each personality keyword is sorted in turn to establish a keyword set. 3.The AI-based electronic business card intelligent generation method of claim 2, wherein, Step S200 includes: Step S210: obtaining the evaluation test result of the target user, taking the selected design elements in the evaluation test result and the professional keywords with a score greater than a score threshold as target keywords, obtaining the design elements of all electronic business card templates, taking a certain electronic business card template as a predetermined template if the design elements of the certain electronic business card template contain at least one of the design elements corresponding to the target keywords, obtaining the keyword set corresponding to the certain predetermined template, and extracting the personality keywords with a serial number less than a serial number threshold in the keyword set as predetermined keywords; Step S220: adding the maximum weight values corresponding to each predetermined keyword to obtain a total weight value, dividing each maximum weight value by the total weight value to obtain a weight ratio corresponding to each predetermined keyword, and then obtaining a weight vector corresponding to a certain predetermined template; Step S230: obtaining the similarity of each predetermined keyword of a certain predetermined template and each professional keyword in the target keywords, normalizing, taking the maximum similarity corresponding to each predetermined keyword as the word weight corresponding to each predetermined keyword, and then obtaining the word vector of the certain predetermined template. The weight vector is multiplied by the word vector to obtain the preference coefficient of the target user and the certain predetermined template, and then the preference coefficient of the target user and each predetermined template is obtained.

4. The artificial intelligence-based electronic business card intelligent generation method according to claim 3, characterized in that, Step S400 includes: Step S410: If the target user does not edit the recommendation template within the recommended time range T, or edits the recommendation template but does not modify all the information contents corresponding to the content editing part, it is determined that the target user is not a user of the recommendation template, and the target user is prompted to input the reason for not using S p and the target preference S q , and set the weight of the target word to be resisted as W p , the weight of the target word of the preference as W q , W p <0<W r <1<W q , wherein W r is the feature weight; Step S420: obtaining all the individual keywords whose serial numbers are less than the serial number threshold in the keyword set corresponding to the certain electronic business card template, and the maximum value of each individual keyword, taking the number of individual keywords as T, and then obtaining the preference coefficient of the certain electronic business card template wherein A is the unused reason S p the number of keywords in the target preference S a that are the same as the individual keywords, W q is the maximum value of the corresponding a th individual keyword, D is the number of keywords in the target preference S d that are the same as the individual keywords, W b is the maximum value of the corresponding b th individual keyword; and then obtaining the preference coefficient of the target user and each electronic business card template, and following the above steps S300 to S400 in this way until the target user determines a suitable electronic business card template.

5. An electronic business card intelligent generation system for performing an artificial intelligence-based electronic business card intelligent generation method according to any one of claims 1-4, characterized in that, The system includes a keyword set obtaining module, a preference coefficient calculation module, a keyword set updating module, and a predetermined electronic business card template module; The keyword set obtaining module is used to obtain the content editing part on each electronic business card template, determine the user corresponding to the electronic business card template and the personality information of the user according to the content change of the content editing part; Each user on the electronic business card platform is evaluated and tested. According to the evaluation test result, the keywords are extracted from the evaluation test content and the personality information, and the keyword set corresponding to each electronic business card template is obtained by analysis; The preference coefficient calculation module is used to extract target keywords according to the evaluation test result of the current target user, obtain the weight vector corresponding to the electronic business card template according to each keyword in the keyword set, obtain the word vector of the electronic business card template according to the similarity of the target keywords and each keyword, and obtain the preference coefficient of the target user and each electronic business card template according to the weight vector and the word vector; The keyword set updating module is configured to obtain a recommended template according to the preference coefficient, recommend the recommended template to the target user, and update the keyword set corresponding to the recommended template if the target user becomes a user of the recommended template. The electronic business card template determining module is configured to prompt the target user to input the influence factor content and analyze the input content if the target user is not a user of the recommended template, and reacquire the preference coefficient of the target user and each electronic business card template, and so on until the target user determines a suitable electronic business card template.

6. The electronic business card intelligent generation system according to claim 5, wherein, The keyword set obtaining module comprises a user obtaining unit, a personal keyword obtaining unit and a keyword set obtaining unit. The user obtaining unit is configured to obtain all electronic business card templates in the electronic business card platform, obtain the user corresponding to each electronic business card template, and obtain the personal information of each user. The personal keyword obtaining unit is configured to perform a judgment test on each user in the electronic business card platform, and then obtain an effective user. If a user corresponding to a certain electronic business card template is an effective user, all personal keywords in the personal information corresponding to the user are obtained. The keyword set obtaining unit is configured to set the weight of each personal keyword, obtain the similarity between each personal keyword and each professional keyword, and obtain the maximum weight of a certain personal keyword.

7. The electronic business card intelligent generation system according to claim 6, wherein, The keyword set updating module comprises a recommended template obtaining unit and a keyword set updating unit. The recommended template obtaining unit is configured to take the electronic business card template corresponding to the maximum preference coefficient as a recommended template, recommend the recommended template to the target user, and obtain all information keywords in the information content corresponding to the modified content editing part if the target user becomes a user of the recommended template within a time range T after the recommendation. The keyword set updating unit is configured to obtain the number of information keywords corresponding to the target user that are the same as the target keyword, and obtain the credibility of the target user. The weights of each predetermined keyword in the recommended template are changed, and each predetermined keyword is reordered according to the changed weights from large to small, and then the keyword set corresponding to the recommended template is updated.

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