Electronic business card intelligent generation system and method based on artificial intelligence

Abstract

The invention discloses an electronic business card intelligent generation system and method based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a content editing part of each electronic business card template, determining each user and personalized information, and obtaining a keyword set corresponding to each electronic business card template; obtaining an evaluation test result of a current target user, extracting a target word, and obtaining a preference coefficient of the target user and each electronic business card template; obtaining a recommendation template according to the preference coefficient, and if the target user becomes a user of the recommendation template, updating a keyword set corresponding to the recommendation template; and if the target user does not become the user, obtaining the preference coefficient again until the target user determines a proper electronic business card template. According to the method, the personalized information of the user is analyzed, the appropriate electronic business card template is recommended for the target user, multi-dimensional data comprehensive analysis is carried out, and the electronic business card template suitable for the personality of the user is more accurately recommended.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an electronic business card intelligent generation system and method based on artificial intelligence. Background Art

[0002] An electronic business card is a digital form of business card, which usually contains basic information of an individual or a company, such as name, position, company name, contact information, address, etc. It can be shared and disseminated 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. When recommending suitable electronic business card templates to users, they often use a single recommendation based on occupation or industry, without fully considering the user's individual factors, such as occupational characteristics, style preferences, etc., resulting in the inability to make intelligent recommendations based on people's personality. Therefore, based on the historical selection records of each template, combined with multi-dimensional data such as user's personality data and preferences for comprehensive analysis, electronic business card templates that suit the user's personality can be recommended more accurately to meet the unique needs and changes of different users. Summary of the invention

[0003] The purpose of the present invention is to provide an electronic business card intelligent generation system and method based on artificial intelligence to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] An intelligent generation method of electronic business cards based on artificial intelligence comprises the following steps:

[0006] Step S100: Obtain the content editing part of each electronic business card template, and determine the user corresponding to the electronic business card template and the user's personal information according to the content change of the content editing part; perform a judgment test on each user on the electronic business card platform, extract keywords from the judgment test content and personal information according to the judgment test results, and analyze them to obtain a keyword set corresponding to each electronic business card template;

[0007] Step S200: extract the target word according to the evaluation test result of the current target user, and 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 word 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;

[0008] Step S300: obtaining a recommended template according to the preference coefficient, and recommending the recommended template to a target user. If the target user becomes a user of the recommended template, updating a keyword set corresponding to the recommended template;

[0009] Step S400: If the target user is not a user of the recommended template, prompt the target user to input influencing factor content, analyze the input content, and re-acquire the preference coefficients of the target user and each electronic business card template, and so on, until the target user determines a suitable electronic business card template.

[0010] Furthermore, step S100 includes:

[0011] Step S110: Acquire 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 all information contents corresponding to the content editing parts on the certain electronic business card template are modified, then the user is regarded as the user of the certain electronic business card template, and the information contents corresponding to the modified content editing parts are regarded as the user's personal information, and all users corresponding to each electronic business card template are obtained;

[0012] Among them, in this plan, the content editing part includes name, position, position keywords, unit, phone number, address information and self-introduction. Among them, the position keywords are determined according to the position. For example, if the position is designer, then the personal keywords are any one or more of the tags such as unlimited creativity, color master, simple fashion, efficient output, strong stress resistance, etc.; for example, if the position is salesperson, then the personal keywords are any one or more of the tags such as communication expert, grasp of customer needs, excellent adaptability, strong stress resistance, etc. The specific keyword tags should be determined according to the actual situation, but the personal professional characteristics should be highlighted;

[0013] Step S120: Conduct a judgment test on each user on the electronic business card platform. The content of the judgment test includes selecting the occupation, scoring each occupation keyword, and selecting the design elements of the electronic business card template. The design elements include color, style and layout. Obtain the judgment test results of each user. If the judgment test time of a certain user is greater than the time threshold, and the scores of each occupation keyword are not the highest or lowest, then the certain user is regarded as a valid user. If a certain user corresponding to a certain electronic business card template is a valid user, obtain all the personality keywords corresponding to the certain user in the personality information.

[0014] In this embodiment, the occupational keyword and the occupation should match each other. The design elements include color, style and layout, where 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; the layout is the overall layout and visual style of the electronic business card template, including horizontal, vertical and square images;

[0015] Step S130: Set the weight of each personality keyword to 1, obtain the similarity between each personality keyword and each occupational keyword, and normalize them, and take the maximum similarity corresponding to a personality keyword as X, and the score of the corresponding occupational keyword when the maximum similarity is X as Y, and then obtain the final weight W=1+[Y*(X-0.5) / K] of a personality keyword, where X∈[0,1], K is the weight coefficient, and K>0; add the weights of the same personality keywords for each user corresponding to a certain electronic business card template, sort the personality keywords in order from large to small in terms of total weight, and establish a keyword set.

[0016] The similarity represents the similarity between a keyword actually input by the user and the occupational keyword of the test. When the maximum similarity X is greater than 0.5, it means that the occupational keyword of the test question is highly consistent with the keyword actually input by 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 final weight W>1 at this time. When the score Y of the occupational keyword of the test question is larger, it means that users with this keyword are more inclined to choose this electronic business card template, and when the score Y of the test question is smaller, it means that users with this keyword are not inclined to choose this electronic business card template.

[0017] Further, step S200 includes:

[0018] Step S210: Obtain the evaluation test results of the target user, and use the design elements selected in the evaluation test results and the occupational keywords with scores greater than the score threshold as target words; obtain the design elements of all electronic business card templates, and if the design elements of a certain electronic business card template include at least one of the design elements corresponding to the target words, use the certain electronic business card template as a predetermined template; obtain a keyword set corresponding to a predetermined template, and extract the individual keywords with sequence numbers less than the sequence number threshold in the keyword set as predetermined keywords;

[0019] Step S220: Add the final weights corresponding to the predetermined keywords to obtain a total weight, and divide the final weights by the total weight to obtain a weight ratio corresponding to each predetermined keyword, and then obtain a weight vector corresponding to a predetermined template;

[0020] Step S230: obtain the similarity between each predetermined keyword of a predetermined template and each occupation keyword in the target word, and normalize them, use the maximum similarity corresponding to each predetermined keyword as the word weight corresponding to each predetermined keyword, and then obtain the word vector of a predetermined template, multiply the weight vector by the word vector, obtain the preference coefficient between the target user and the predetermined template, and then obtain the preference coefficient between 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 used by the user. The higher the weight, the more the corresponding keyword can be used to represent the electronic business card template.

[0022] Furthermore, step S300 includes:

[0023] Step S310: The electronic business card template corresponding to the maximum preference coefficient is used as a recommended template, and the recommended template is recommended to the target user. If the target user becomes a user of the recommended template within a 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: Obtain the number N of information keywords corresponding to the target user that are identical to the target word, and obtain the credibility of the target user F=1-e -H*N , where e is the natural index and H is the preset credibility coefficient; according to the credibility level F, the weights of each predetermined keyword in the recommendation template are changed, and the changed weights are W0+(1+F*M), where W0 is the initial weight of a predetermined keyword, and M is the word weight corresponding to a predetermined keyword. The weights of each predetermined keyword after the change are re-sorted in descending order, and then the keyword set corresponding to the recommendation template is updated.

[0025] Furthermore, step S400 includes:

[0026] Step S410: If the target user does not edit based on the recommended template within the time range T after recommendation, or edits based on the recommended template but does not modify all the information corresponding to the content editing part, it is determined that the target user is not a user of the recommended template, and the target user is prompted to enter the reason for non-use S p and target preference S q , and set the weight of the resisted target word to W p , the weight of the preferred target word is W q , W p <0<W r <1<W q , where W r is the feature weight;

[0027] Step S420: Obtain all individual keywords whose sequence numbers are less than the sequence number threshold in the keyword set corresponding to a certain electronic business card template, as well as the final weight of each individual keyword, and take the number of individual keywords as T to obtain the preference coefficient of a certain electronic business card template. Among them, A is the reason for non-use S p The number of keywords in the same as the personality keywords, W a is the final weight of the corresponding a-th personality keyword, D is the target preference Sq The number of keywords in the same as the personality keywords, W d is the final weight of the corresponding dth personality keyword, B is the number of characteristic keywords, B = TAD, W b is the final weight of the corresponding b-th personalized keyword; and then the preference coefficients of the target user and each electronic business card template are obtained, and the above steps S300 to S400 are repeated and so on until the target user determines a suitable electronic business card template.

[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 an electronic business card template determination module;

[0029] Obtaining keyword set module: used to obtain the content editing part of each electronic business card template, determine the user corresponding to the electronic business card template and the user's personal information according to the content change of the content editing part; conduct a judgment test on each user on the electronic business card platform, extract keywords from the judgment test content and personal information according to the judgment test results, and analyze and obtain the keyword set corresponding to each electronic business card template;

[0030] Preference coefficient calculation module: used to extract the target word according to the evaluation test results of the current target user, and 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 word 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] Keyword set update module: used to obtain a recommendation template according to the preference coefficient, and recommend the recommendation template to the target user. If the target user becomes a user of the recommendation template, the keyword set corresponding to the recommendation template is updated;

[0032] Determine electronic business card template module: If the target user is not a user of the recommended template, the electronic business card template determination module is used to prompt the target user to input influencing factor content, analyze the input content, and re-obtain 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 module for obtaining a keyword set includes obtaining a user unit, obtaining a personalized keyword unit and obtaining a keyword set unit;

[0034] Obtaining user unit: used to obtain all electronic business card templates in the electronic business card platform, obtain the user corresponding to each electronic business card template, and the personal information of each user;

[0035] Obtaining personalized keywords unit: used to conduct a judgment test on each user on the electronic business card platform, and then obtain valid users; if a user corresponding to a certain electronic business card template is a valid user, obtain all personalized keywords in the personalized information corresponding to the user;

[0036] Obtain keyword set unit: used to set the weight of each sex keyword, obtain the similarity between each sex keyword and each occupation keyword, and obtain the final weight of a sex keyword.

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

[0038] Obtaining recommended template unit: used to take the electronic business card template corresponding to the maximum preference coefficient as the recommended template, and recommend the recommended template to the target user. If the target user becomes the user of the recommended template within the time range T after the recommendation, all the information keywords in the information content corresponding to the modified content editing part are obtained;

[0039] Keyword set updating unit: used to obtain the number of information keywords corresponding to the target user that is the same as the target word, and obtain the credibility of the target user; change the weight of each predetermined keyword in the recommendation template, and re-sort the changed weights of each predetermined keyword from large to small, and then update the keyword set corresponding to the recommendation template.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides an electronic business card intelligent generation system and method based on artificial intelligence, including: obtaining the content editing part of each electronic business card template, determining each user and personality information, and obtaining a keyword set corresponding to each electronic business card template; obtaining the evaluation test results of the current target user, extracting the target word, and obtaining the preference coefficient between the target user and each electronic business card template; obtaining a recommended template according to the preference coefficient, and if the target user becomes a user of the recommended template, the keyword set corresponding to the recommended template is updated; if the target user does not become a user, the preference coefficient is re-obtained until the target user determines a suitable electronic business card template. The present invention recommends a suitable electronic business card template to the target user by analyzing the user's personality information, and performs a comprehensive analysis based on the user's personality data, preferences and other multi-dimensional data, so as to more accurately recommend an electronic business card template suitable for the user's personality and meet the unique needs and changes of different users. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic diagram of a process of an electronic business card intelligent generation method based on artificial intelligence of the present invention;

[0042] Figure 2The present invention is a structural diagram of an electronic business card intelligent generation system based on artificial intelligence. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Example: Figure 1 As shown, the present invention provides a technical solution of an electronic business card intelligent generation system and method based on artificial intelligence, comprising the following steps:

[0045] Step S100: Obtain the content editing part of each electronic business card template, and determine the user corresponding to the electronic business card template and the user's personal information based on the content changes in the content editing part; perform a judgment test on each user on the electronic business card platform, and based on the judgment test results, extract keywords from the judgment test content and personal information, and analyze them to obtain a keyword set corresponding to each electronic business card template.

[0046] Step S110: Acquire 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, then the user is regarded as the user of the certain electronic business card template, and the information content corresponding to the modified content editing part is regarded as the personal information of the user, and all users corresponding to each electronic business card template are obtained.

[0047] Among them, in this plan, the content editing part includes name, position, position keywords, unit, telephone number, address information and self-introduction. Among them, the position keywords are determined according to the position. For example, if the position is designer, then the personal keywords are any one or more of the tags such as unlimited creativity, color master, simple fashion, efficient output, strong pressure resistance, etc.; for example, if the position is salesperson, then the personal keywords are any one or more of the tags such as communication expert, grasp of customer needs, excellent adaptability, strong pressure resistance, etc. The specific keyword tags should be determined according to the actual situation, but the personal professional characteristics should be highlighted.

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

[0049] In this embodiment, the occupational keywords and occupations should match each other, and the design elements include color, style and layout, among which 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.; the layout is the overall layout and visual style of the electronic business card template, including horizontal, vertical and square images, etc.

[0050] Step S130: Set the weight of each personality keyword to 1, obtain the similarity between each personality keyword and each occupational keyword, and normalize them, and take the maximum similarity corresponding to a personality keyword as X, and the score of the corresponding occupational keyword when the maximum similarity is X as Y, and then obtain the final weight W=1+[Y*(X-0.5) / K] of a personality keyword, where X∈[0,1], K is the weight coefficient, and K>0; add the weights of the same personality keywords for each user corresponding to a certain electronic business card template, sort the personality keywords in order from large to small in terms of total weight, and establish a keyword set.

[0051] The similarity represents the similarity between a keyword actually input by the user and the occupational keyword of the test. When the maximum similarity X is greater than 0.5, it means that the occupational keyword of the test question is highly consistent with the keyword actually input by 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 final weight W>1 at this time. When the score Y of the occupational keyword of the test question is large, it means that users with the keyword are more inclined to choose the electronic business card template, and when the score Y of the test question is small, it means that users with the keyword are not inclined to choose the electronic business card template. In this embodiment, the scoring is based on a ten-point system, that is, Y∈[0,10], and the weight coefficient K=10.

[0052] Step S200: extract the target word according to the evaluation test result of the current target user, and 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 word 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;

[0053] Step S210: Obtain the evaluation test results of the target user, and use the design elements selected in the evaluation test results and the occupational keywords with scores greater than the score threshold as target words; obtain the design elements of all electronic business card templates, and if the design elements of an electronic business card template contain at least one of the design elements corresponding to the target words, use the electronic business card template as a predetermined template; obtain a keyword set corresponding to a predetermined template, and extract the personalized keywords with serial numbers less than the serial number threshold in the keyword set as predetermined keywords.

[0054] Step S220: Add the final weights corresponding to the predetermined keywords to obtain a total weight, and divide the final weights by the total weight to obtain a weight ratio corresponding to each predetermined keyword, and then obtain a weight vector corresponding to a predetermined template.

[0055] Step S230: obtain the similarity between each predetermined keyword of a predetermined template and each occupation keyword in the target word, and normalize them, use the maximum similarity corresponding to each predetermined keyword as the word weight corresponding to each predetermined keyword, and then obtain the word vector of a predetermined template, multiply the weight vector by the word vector, obtain the preference coefficient between the target user and the predetermined template, and then obtain the preference coefficient between 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. The higher the weight, the more the corresponding keyword can be used to represent the electronic business card template.

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

[0058] Step S310: The electronic business card template corresponding to the maximum preference coefficient is used as a recommended template, and the recommended template is recommended to the target user. If the target user becomes a user of the recommended template within a time range T after the recommendation, all information keywords in the information content corresponding to the modified content editing part are obtained;

[0059] Step S320: Obtain the number N of information keywords corresponding to the target user that are identical to the target word, and obtain the credibility of the target user F=1-e -H*N, where e is the natural index and H is the preset credibility coefficient; according to the credibility level F, the weights of each predetermined keyword in the recommendation template are changed, and the changed weights are W0+(1+F*M), where W0 is the initial weight of a predetermined keyword, and M is the word weight corresponding to a predetermined keyword. The weights of each predetermined keyword after the change are re-sorted in descending order, and then the keyword set corresponding to the recommendation template is updated.

[0060] Step S400: If the target user is not a user of the recommended template, prompt the target user to input influencing factor content, analyze the input content, and re-acquire the preference coefficients of the target user and each electronic business card template, and so on, until the target user determines a suitable electronic business card template.

[0061] Step S410: If the target user does not edit based on the recommended template within the time range T after recommendation, or edits based on the recommended template but does not modify all the information corresponding to the content editing part, it is determined that the target user is not a user of the recommended template, and the target user is prompted to enter the reason for non-use S p and target preference S q , and set the weight of the resisted target word to W p , the weight of the preferred target word is W q , W p <0<W r <1<W q , where W r is the feature weight;

[0062] Among them, the influencing factors include reasons for non-use and target preference.

[0063] Step S420: Obtain all individual keywords whose sequence numbers are less than the sequence number threshold in the keyword set corresponding to a certain electronic business card template, as well as the final weight of each individual keyword, and take the number of individual keywords as T to obtain the preference coefficient of a certain electronic business card template. Among them, A is the reason for non-use S p The number of keywords in the same as the personality keywords, W a is the final weight of the corresponding a-th personality keyword, D is the target preference S q The number of keywords in the same as the personality keywords, W d is the final weight of the corresponding dth personality keyword, B is the number of characteristic keywords, B = TAD, W b is the final weight of the corresponding b-th personalized keyword; and then the preference coefficients of the target user and each electronic business card template are obtained, and the above steps S300 to S400 are repeated and so on until the target user determines a suitable electronic business card template.

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

[0065] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An intelligent generation method of electronic business cards based on artificial intelligence, characterized in that: The following steps are involved: Step S100: obtaining the content editing part of each electronic business card template, and determining the user corresponding to the electronic business card template and the user's personal information according to the content change of the content editing part; Conduct a judgment test on each user on the electronic business card platform, extract keywords from the judgment test content and personal information based on the judgment test results, and analyze them to obtain a keyword set corresponding to each electronic business card template; Step S200: extract the target word according to the evaluation test result of the current target user, and 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 word 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; Step S300: obtaining a recommended template according to the preference coefficient, and recommending the recommended template to a target user. If the target user becomes a user of the recommended template, updating a keyword set corresponding to the recommended template; Step S400: If the target user is not a user of the recommended template, prompt the target user to input influencing factors, analyze the input content, and re-acquire the preference coefficients of the target user and each electronic business card template, and so on, until the target user determines a suitable electronic business card template.

2. The method for intelligently generating electronic business cards based on artificial intelligence according to claim 1, characterized in that: Step S100 includes: Step S110: Acquire 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 all information contents corresponding to the content editing parts on the certain electronic business card template are modified, then the user is regarded as the user of the certain electronic business card template, and the information contents corresponding to the modified content editing parts are regarded as the user's personal information, and all users corresponding to each electronic business card template are obtained; Step S120: Conduct a judgment test on each user on the electronic business card platform. The content of the judgment test includes selecting the occupation, scoring each occupation keyword, and selecting the design elements of the electronic business card template. The design elements include color, style and layout. Obtain the judgment test results of each user. If the judgment test time of a certain user is greater than the time threshold, and the scores of each occupation keyword are not the highest or lowest, then the certain user is regarded as a valid user. If a certain user corresponding to a certain electronic business card template is a valid user, obtain all the personality keywords corresponding to the personality information of the certain user. Step S130: Set the weight of each personality keyword to 1, obtain the similarity between each personality keyword and each occupational keyword, and normalize them, and take the maximum similarity corresponding to a personality keyword as X, and the score of the corresponding occupational keyword when the maximum similarity is X as Y, and then obtain the final weight W=1+[Y*(X-0.5) / K] of a personality keyword, where X∈[0,1], K is the weight coefficient, and K>0; add the weights of the same personality keywords for each user corresponding to a certain electronic business card template, sort the personality keywords in order from large to small in terms of total weight, and establish a keyword set.

3. The method for intelligently generating electronic business cards based on artificial intelligence according to claim 2, characterized in that: Step S200 includes: Step S210: Obtain the evaluation test results of the target user, and use the design elements selected in the evaluation test results and the occupational keywords with scores greater than the score threshold as target words; obtain the design elements of all electronic business card templates, and if the design elements of a certain electronic business card template include at least one of the design elements corresponding to the target words, use the certain electronic business card template as a predetermined template; obtain a keyword set corresponding to a predetermined template, and extract the individual keywords with sequence numbers less than the sequence number threshold in the keyword set as predetermined keywords; Step S220: Add the final weights corresponding to the predetermined keywords to obtain a total weight, and divide the final weights by the total weight to obtain a weight ratio corresponding to each predetermined keyword, and then obtain a weight vector corresponding to a predetermined template; Step S230: obtain the similarity between each predetermined keyword of a predetermined template and each occupation keyword in the target word, and normalize them, use the maximum similarity corresponding to each predetermined keyword as the word weight corresponding to each predetermined keyword, and then obtain the word vector of the predetermined template, multiply the weight vector by the word vector, obtain the preference coefficient between the target user and the predetermined template, and then obtain the preference coefficient between the target user and each predetermined template.

4. The method for intelligently generating electronic business cards based on artificial intelligence according to claim 3, characterized in that: Step S300 includes: Step S310: The electronic business card template corresponding to the maximum preference coefficient is used as a recommended template, and the recommended template is recommended to the target user. If the target user becomes a user of the recommended template within a time range T after the recommendation, all information keywords in the information content corresponding to the modified content editing part are obtained; Step S320: Obtain the number N of information keywords corresponding to the target user that are identical to the target word, and obtain the credibility of the target user F=1-e -H*N , where e is the natural index and H is the preset credibility coefficient; according to the credibility level F, the weights of each predetermined keyword in the recommendation template are changed, and the changed weights are W0+(1+F*M), where W0 is the initial weight of a predetermined keyword, and M is the word weight corresponding to a predetermined keyword. The weights of each predetermined keyword after the change are re-sorted in descending order, and then the keyword set corresponding to the recommendation template is updated.

5. The method for intelligently generating electronic business cards based on artificial intelligence according to claim 4, characterized in that: Step S400 includes: Step S410: If the target user does not edit based on the recommended template within the time range T after recommendation, or edits based on the recommended template but does not modify all the information corresponding to the content editing part, it is determined that the target user is not a user of the recommended template, and the target user is prompted to enter the reason for non-use S p and target preference S q , and set the weight of the resisted target word to W p , the weight of the preferred target word is W q , W p <0<W r <1<W q , where W r is the feature weight; Step S420: Obtain all individual keywords whose sequence numbers are less than the sequence number threshold in the keyword set corresponding to a certain electronic business card template, as well as the final weight of each individual keyword, and take the number of individual keywords as T to obtain the preference coefficient of a certain electronic business card template. Among them, A is the reason for non-use S p The number of keywords in the same as the personality keywords, W a is the final weight of the corresponding a-th personality keyword, D is the target preference S q The number of keywords in the same as the personality keywords, W d is the final weight of the corresponding dth personality keyword, B is the number of characteristic keywords, B = TAD, W b is the final weight of the corresponding b-th personalized keyword; and then the preference coefficients of the target user and each electronic business card template are obtained, and the above steps S300 to S400 are repeated and so on until the target user determines a suitable electronic business card template.

6. An electronic business card intelligent generation system, used to execute an electronic business card intelligent generation method based on artificial intelligence as described in any one of claims 1 to 5, characterized in that: The system includes a module for obtaining a keyword set, a module for calculating a preference coefficient, a module for updating a keyword set, and a module for determining an electronic business card template; Obtaining keyword set module: used to obtain the content editing part of each electronic business card template, and determine the user corresponding to the electronic business card template and the user's personal information according to the content change of the content editing part; Conduct a judgment test on each user on the electronic business card platform, extract keywords from the judgment test content and personal information based on the judgment test results, and analyze them to obtain a keyword set corresponding to each electronic business card template; Preference coefficient calculation module: used to extract the target word according to the evaluation test results of the current target user, and 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 word 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; Keyword set updating module: used to obtain a recommendation template according to the preference coefficient, recommend the recommendation template to the target user, and if the target user becomes a user of the recommendation template, update the keyword set corresponding to the recommendation template; Determine the electronic business card template module: If the target user is not a user of the recommended template, the electronic business card template determination module is used to prompt the target user to input influencing factor content, analyze the input content, and re-obtain 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.

7. The electronic business card intelligent generation system according to claim 6, characterized in that: The module for obtaining a keyword set includes a unit for obtaining a user, a unit for obtaining a personalized keyword, and a unit for obtaining a keyword set; Obtaining user unit: used to obtain all electronic business card templates in the electronic business card platform, obtain the user corresponding to each electronic business card template, and the personal information of each user; Obtaining personalized keyword units: used to conduct a judgment test on each user on the electronic business card platform, and then obtain valid users; If a user corresponding to a certain electronic business card template is a valid user, all the personality keywords in the personality information corresponding to the certain user are obtained; Obtain keyword set unit: used to set the weight of each sex keyword, obtain the similarity between each sex keyword and each occupation keyword, and obtain the final weight of a sex keyword.

8. The electronic business card intelligent generation system according to claim 7, characterized in that: The keyword set updating module includes a recommendation template obtaining unit and a keyword set updating unit; The recommended template acquisition unit is used to take the electronic business card template corresponding to the maximum preference coefficient as the recommended template, and recommend the recommended template to the target user. If the target user becomes the user of the recommended template within the time range T after the recommendation, all the information keywords in the information content corresponding to the modified content editing part are obtained; Keyword set updating unit: used to obtain the number of information keywords corresponding to the target user that are the same as the target word, and obtain the credibility of the target user; The weights of the predetermined keywords in the recommendation template are changed, and the keywords are reordered from large to small according to the changed weights of the predetermined keywords, so as to update the keyword set corresponding to the recommendation template.

Images