A visual website construction promotion method and promotion system

Abstract

The present invention belongs to the technical field of website construction and promotion, and specifically relates to a visualized website construction and promotion method and promotion system. The invention can interact with visiting users in a visualized manner, so that users can intuitively understand the content of website construction and promotion, improve user experience, and obtain personalized recommended content by using a correlation index to evaluate the parameters to be evaluated and determine key access fields and non-key access fields. After the interaction is completed, it can also capture the user's access information and feedback in real time, continuously adjust and optimize the recommended content, and form a closed-loop optimization system, thereby increasing the website's visits, user stickiness, conversion rate, and user satisfaction, and achieving the goal of website construction and promotion.

Description

Technical Field

[0001] The invention belongs to the technical field of website construction and promotion, and in particular relates to a visualized website construction and promotion method and promotion system. Background Art

[0002] With the popularization and development of the Internet, more and more companies and individuals have begun to build their own websites to showcase their products, services and brand image. However, due to the huge amount of information on the Internet, how to make one's website stand out from many competitors and attract the attention of potential customers has become a major challenge for website builders and promoters. In order to solve this problem, people have developed many website construction and promotion methods, such as search engine optimization (SEO), search engine marketing (SEM), social media marketing, etc., to increase the popularity and traffic of the website.

[0003] However, traditional website construction and promotion methods often lack intuitiveness and visual interactive effects. For example, SEO and SEM mainly rely on keyword rankings and advertising, and it is difficult for users to intuitively understand the content and characteristics of the website. In addition, these methods usually take a long time to see results and cannot quickly increase the visibility of a company or individual. They have great limitations. Based on this, this solution provides a visual interactive website construction and promotion method. Summary of the invention

[0004] The purpose of the present invention is to provide a visual website construction promotion method and promotion system, which can visually interact with visiting users, capture users' access information and feedback in real time, and continuously adjust and optimize recommended content.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A visual website construction promotion method and promotion system, comprising:

[0007] Obtaining the user's access information, wherein the access information includes access duration, access times, access content, and access target;

[0008] Performing classification extraction on the access content to obtain key access fields and non-key access fields, and then inputting the key access fields and non-key access fields into a pairing model to obtain recommended content;

[0009] Acquiring user feedback information on the recommended content, the feedback information including an interactive response rate and feedback satisfaction, wherein the feedback satisfaction includes satisfactory feedback and unsatisfactory feedback;

[0010] The interactive response rate and feedback satisfaction are input into the evaluation model together to obtain a promotion score, and the website construction promotion content is optimized based on the promotion score.

[0011] In a preferred solution, the step of performing classification extraction on the access content to obtain key access fields and non-key access fields includes:

[0012] Acquire the access content, perform word segmentation processing on it, obtain multiple independent words, perform vector conversion on each of the independent words, obtain multiple numerical vectors, and mark them as parameters to be evaluated;

[0013] Inputting the parameters to be evaluated into the evaluation model to obtain the correlation index of each parameter to be evaluated;

[0014] Obtaining an evaluation threshold and comparing it with the correlation index;

[0015] If the correlation index is greater than or equal to the evaluation threshold, the corresponding parameter to be evaluated is marked as a key access field;

[0016] If the correlation index is less than the evaluation threshold, the corresponding parameter to be evaluated is marked as a non-critical access field.

[0017] In a preferred embodiment, the step of inputting the parameters to be evaluated into the evaluation model to obtain the correlation index of each parameter to be evaluated includes:

[0018] Obtaining all the parameters to be evaluated and the benchmark keywords under the access target;

[0019] Calling an evaluation function from the evaluation model;

[0020] The parameter to be evaluated and the benchmark keyword are input into an evaluation function, and the output result is calibrated as the correlation index of the parameter to be evaluated.

[0021] In a preferred embodiment, the step of inputting the key access field and the non-key access field into a pairing model to obtain recommended content includes:

[0022] Acquire the key access field and the non-key access field;

[0023] Calling the response information corresponding to the access target from the pairing model, wherein the response information includes a response text, a response picture and a video;

[0024] All response information corresponding to the key access field and the non-key access field is obtained, and response output is performed according to the correlation index corresponding to each response information, and the output content is marked as recommended content.

[0025] In a preferred solution, the step of outputting a response according to the correlation index corresponding to each response information includes:

[0026] Acquire all response information corresponding to the key access field and the non-key access field, wherein the same response information corresponds to several key access fields and non-key access fields;

[0027] The correlation indexes of the key access fields and the non-key access fields in each of the response information are summarized to obtain a total correlation degree, and the total correlation degrees are arranged from large to small according to their values, and then the corresponding response information is output one by one in this order.

[0028] In a preferred solution, the step of obtaining user feedback information on the recommended content includes:

[0029] Get the user's access time in real time;

[0030] Obtaining a standard duration and comparing it with the access duration, and generating a greeting statement when the access duration is greater than or equal to the standard duration;

[0031] Counting the number of times the greeting statement is issued and the number of times the user responds, performing a combined operation, and marking the operation result as an interactive response rate;

[0032] After the interaction is completed, a satisfaction rating list is generated, and user feedback ratings are counted based on the satisfaction rating list, and user satisfaction is determined based on the feedback ratings.

[0033] In a preferred embodiment, the step of determining user satisfaction based on the feedback score includes:

[0034] Construct a monitoring period and count the feedback scores of all users within the monitoring period;

[0035] Obtaining a satisfaction evaluation threshold and comparing it with the feedback score;

[0036] If the feedback score is greater than or equal to the satisfaction evaluation threshold, it indicates that the user is highly satisfied with the recommended content, and it is marked as satisfactory feedback;

[0037] If the feedback score is less than the satisfaction evaluation threshold, it indicates that the user is less satisfied with the recommended content, and it is marked as unsatisfactory feedback.

[0038] In a preferred embodiment, the step of inputting the interactive response rate and the feedback satisfaction into an evaluation model to obtain a promotion score includes:

[0039] Obtaining the interactive response rate, and marking it as a first parameter to be evaluated;

[0040] Obtain the percentage of satisfactory feedback and mark it as the second parameter to be evaluated;

[0041] Calling an evaluation function from the evaluation model, inputting the first parameter to be evaluated and the second parameter to be evaluated into the evaluation function, and marking the output result as a promotion score;

[0042] Retrieving an evaluation threshold from the evaluation model, and comparing the evaluation threshold with the promotion score;

[0043] If the promotion score is greater than or equal to the evaluation threshold, there is no need to optimize the website construction promotion content;

[0044] If the promotion score is less than the evaluation threshold, the website construction promotion content is optimized.

[0045] The present invention also provides a visualized website construction promotion system, which is applied to the above-mentioned visualized website construction promotion method, comprising:

[0046] An information collection module, the information collection module is used to obtain the user's access information, wherein the access information includes access duration, access times, access content and access target;

[0047] A recommendation module, the recommendation module is used to perform classification extraction on the access content to obtain key access fields and non-key access fields, and then input the key access fields and non-key access fields into a pairing model to obtain recommended content;

[0048] A feedback module, the feedback module is used to obtain user feedback information on the recommended content, the feedback information includes an interactive response rate and feedback satisfaction, wherein the feedback satisfaction includes satisfactory feedback and unsatisfactory feedback;

[0049] An evaluation module is used to input the interactive response rate and feedback satisfaction into an evaluation model to obtain a promotion score, and optimize the website construction promotion content according to the promotion score.

[0050] And, a visual website construction promotion device, comprising:

[0051] at least one processor;

[0052] and a memory communicatively coupled to the at least one processor;

[0053] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned visualized website construction and promotion method.

[0054] The technical effects achieved by the present invention are:

[0055] The present invention can interact with visiting users in a visual manner, so that users can intuitively understand the content of website construction and promotion, improve user experience, and obtain personalized recommended content by adopting the correlation index to evaluate the parameters to be evaluated and determining the key access fields and non-key access fields. After the interaction is completed, the user's access information and feedback opinions can be captured in real time, and the recommended content can be continuously adjusted and optimized to form a closed-loop optimization system, thereby increasing the website's visits, user stickiness, conversion rate and user satisfaction, and achieving the goal of website construction and promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flow chart of the method provided by the present invention;

[0057] Figure 2 It is a system module diagram provided by the present invention;

[0058] Figure 3 It is a terminal structure diagram provided by the present invention. DETAILED DESCRIPTION

[0059] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0060] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0061] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0062] See also Figure 1 As shown, the present invention provides a visual website construction and promotion method, comprising:

[0063] S1. Obtaining the user's access information, wherein the access information includes access duration, access times, access content, and access target;

[0064] S2. Perform classification extraction on the access content to obtain key access fields and non-key access fields, and then input the key access fields and non-key access fields into the pairing model to obtain recommended content;

[0065] S3. Obtaining user feedback information on the recommended content, where the feedback information includes an interactive response rate and feedback satisfaction, where the feedback satisfaction includes satisfactory feedback and unsatisfactory feedback;

[0066] S4. Input the interactive response rate and feedback satisfaction into the evaluation model together to obtain the promotion score, and optimize the website construction promotion content based on the promotion score.

[0067] As described in the above steps S1-S4, in today's era of network information explosion, website construction and promotion have become important tasks for major enterprises and individuals. In order to improve the promotion effect of website construction, this solution proposes a visual website construction and promotion method, which mainly includes the following four steps: data collection, content recommendation, user feedback and promotion optimization. First, it is necessary to obtain the user's access information. This access information includes access time, number of visits, access content and access target. By collecting this information, the user's interests and needs can be understood to prepare for subsequent content recommendation. Then, the access content is classified and extracted to distinguish key access fields from non-key access fields. Key access fields usually include products, services, topics, etc. that users are concerned about, while non-key access fields include some irrelevant words used for coherent sentences. Then, these key access fields and non-key access fields are input into the pairing model to obtain recommended content. At this time, the generated recommended content can be pushed to the user to achieve the goal of personalized recommendation. In order to continuously optimize the recommendation effect, it is also necessary to obtain user feedback information on the recommended content. This feedback information includes interactive response rate and feedback satisfaction. The interactive response rate refers to the user's interaction with the website after receiving the recommended content, such as clicks, comments, sharing, etc. Feedback satisfaction includes satisfactory feedback and unsatisfactory feedback, which are collected through user ratings and other methods. Finally, the interactive response rate and feedback satisfaction are input into the evaluation model together to obtain the promotion score. This score represents the effectiveness of website construction and promotion. The website construction and promotion content can be optimized according to the score. The optimization methods can include adjusting content strategies, improving page design, and increasing page loading speed. Through continuous optimization, it aims to increase website visits, user stickiness and conversion rate, thereby achieving the goal of website construction and promotion.

[0068] In a preferred embodiment, the step of performing classification extraction on the access content to obtain key access fields and non-key access fields includes:

[0069] S201, obtaining access content, and performing word segmentation processing on it to obtain multiple independent words, and then performing vector conversion on each independent word to obtain multiple numerical vectors, and marking them as parameters to be evaluated;

[0070] S202, inputting the parameters to be evaluated into the evaluation model to obtain the correlation index of each parameter to be evaluated;

[0071] S203, obtaining an evaluation threshold and comparing it with the correlation index;

[0072] If the correlation index is greater than or equal to the evaluation threshold, the corresponding parameter to be evaluated is marked as a key access field;

[0073] If the correlation index is less than the evaluation threshold, the corresponding parameter to be evaluated is marked as a non-critical access field.

[0074] As described in the above steps S201-S201, when extracting key access fields and non-key access fields, it is first necessary to perform word segmentation on the access content. Word segmentation is to extract independent words from the original text. After the word segmentation, each independent word needs to be vectorized and converted into a numerical vector. This process is similar to mapping the text to a multidimensional space. Each word has a corresponding position in this space. In this way, we get a set of parameters to be evaluated. Next, these parameters to be evaluated are input into the evaluation model. The evaluation model will calculate their correlation index based on the degree of correlation between these parameters. The correlation index represents the degree of correlation between the parameters to be evaluated and the access content. The higher the index, the more important they are. Then, an evaluation threshold needs to be set to determine whether the correlation index is high enough to mark the parameters to be evaluated as key access fields. If the correlation index is greater than or equal to the evaluation threshold, then the parameter to be evaluated is considered to be a key access field. If the correlation index is less than the evaluation threshold, then it is marked as a non-key access field.

[0075] Secondly, the step of inputting the parameters to be evaluated into the evaluation model to obtain the correlation index of each parameter to be evaluated includes:

[0076] Step 1: Get all parameters to be evaluated and access the benchmark keywords under the target;

[0077] Step 2. Call the evaluation function from the evaluation model;

[0078] Step 3: Input the parameter to be evaluated and the benchmark keyword into the evaluation function, and calibrate the output result as the correlation index of the parameter to be evaluated.

[0079] As described in the above step Step 1-Step 1, when determining the correlation index evaluation of the parameters to be evaluated, first collect and organize all the parameters to be evaluated. At the same time, deeply understand the access target field and extract the benchmark keywords under the access target. These benchmark keywords should be highly representative and authoritative so that they can accurately reflect the correlation degree of the parameters to be evaluated in the subsequent evaluation process. Then, call the evaluation function from the evaluation model to calculate the correlation index of the parameters to be evaluated, where the expression of the evaluation function is: In the formula, r represents the correlation index, x i Represents the parameter to be evaluated, y i represents the numerical vector corresponding to the benchmark keyword, n represents the number of features in the parameter to be evaluated and the benchmark keyword, represents the parameter to be evaluated, It represents the mean of the numerical vector corresponding to the benchmark keyword. Based on this, the correlation index between the parameter to be evaluated and the benchmark keyword can be determined, providing corresponding data support for the subsequent generation of recommended content.

[0080] In a preferred embodiment, the step of inputting the key access field and the non-key access field into the pairing model to obtain the recommended content includes:

[0081] S204, obtaining key access fields and non-key access fields;

[0082] S205, calling the response information corresponding to the access target from the matching model, wherein the response information includes a response text, a response picture and a video;

[0083] S206: Acquire all response information corresponding to the key access field and the non-key access field, and perform response output according to the correlation index corresponding to each response information, and mark the output content as recommended content.

[0084] As described in the above steps S204-S206, after obtaining the key access fields and non-key access fields, these data need to be input into the pairing model. Next, the response information corresponding to the access target is called from the pairing model. The response information includes response text, response pictures and videos, etc. Then, all the response information corresponding to the key access fields and non-key access fields needs to be obtained. These response information contain rich recommended content and can provide users with diverse choices. On this basis, the response output is performed according to the correlation index corresponding to each response information. The correlation index reflects the degree of matching between the response information and the user's needs. The higher the correlation index, the more the recommended content meets the user's needs. Finally, the output content is marked as recommended content. These recommended contents are sorted and screened according to the user's key access fields and non-key access fields and the correlation index of the response information, and have a high degree of personalization and accuracy.

[0085] In a preferred embodiment, the step of outputting a response according to the correlation index corresponding to each response information includes:

[0086] Step 4, obtain all response information corresponding to the key access field and the non-key access field, where the same response information corresponds to several key access fields and non-key access fields;

[0087] Step 5. Summarize the correlation indexes of the key access fields and non-key access fields in each response information to obtain the total correlation degree, and arrange the total correlation degrees from large to small according to their values, and then output the corresponding response information one by one in this order.

[0088] As described in the above steps Step 4-Step 5, first, it is necessary to obtain all the response information corresponding to the key access field and the non-key access field. In actual applications, the same response information may correspond to several key access fields and non-key access fields. This is because a response information may involve multiple aspects of content, and these contents may be included in key access fields and non-key access fields of different importance. Next, the correlation index of the key access field and the non-key access field in each response information is summarized. The correlation index is an indicator to measure the degree of correlation between two elements. It can reflect the degree of correlation between a response information and the key access field and the non-key access field. By summarizing the correlation index, we can get the total correlation degree, which represents the correlation degree of all key access fields. A comprehensive evaluation of the degree of correlation between fields and non-critical access fields. After obtaining the total correlation, it is necessary to arrange them from large to small according to their values. In this way, each response information can be prioritized according to the size of the correlation. The greater the correlation, the higher the correlation between the key access fields and the non-key access fields in the response information. Therefore, the response information with higher priority can better meet the needs of users. Finally, the output is executed one by one in the order of high to low correlation, that is, when the user repeats the inquiry, the next response information is output. In this process, it is necessary to select the response information that best meets the user's needs according to the key access fields and non-key access fields entered by the user for output. In this way, the accuracy and real-time performance of the output results can be ensured, thereby improving the intelligence level of human-computer interaction.

[0089] In a preferred embodiment, the step of obtaining user feedback information on the recommended content includes:

[0090] S301, obtaining the user's access time in real time;

[0091] S302, obtaining the standard duration and comparing it with the access duration, and generating a greeting statement when the access duration is greater than or equal to the standard duration;

[0092] S303, counting the number of times the greeting statement is sent and the number of times the user responds, performing a combined operation, and marking the operation result as an interactive response rate;

[0093] S304: After the interaction is completed, a satisfaction rating list is generated, and user feedback ratings are counted based on the satisfaction rating list, and user satisfaction is determined based on the feedback ratings.

[0094] As described in the above steps S301-S304, the user's access time is obtained in real time. In order to understand the user's interest in the recommended content, it is necessary to pay attention to their stay time when browsing the recommended content, and then formulate a standard time and compare it with the access time. The access time is an important indicator of the user's interest in the recommended content. A standard time, such as the average access time, can be formulated based on historical data. When the user's access time is greater than or equal to the standard time, it is considered that the user is interested in the recommended content. At this time, a greeting statement can be generated to the user, and the user's response is waited for. Then, the number of times the greeting statement is issued and the number of times the user responds are counted, and a combined operation is performed. The purpose of this step is to calculate the user's interactive response rate (interactive response rate = number of user responses / number of times the greeting statement is issued). After the interaction is completed, a satisfaction rating list is generated, and the user's feedback rating is counted. The satisfaction rating is an important indicator to measure the user's satisfaction with the recommended content. After the interaction is completed, the user can be asked to rate the recommended content, such as using 1 to 5 points to indicate the degree of satisfaction. Then, the user's average rating is counted according to the satisfaction rating list to measure the user's satisfaction with the recommended content.

[0095] Secondly, the steps to determine user satisfaction based on feedback scores include:

[0096] Step 1: Construct a monitoring period and count the feedback scores of all users within the monitoring period;

[0097] Step 2: Obtain the satisfaction evaluation threshold and compare it with the feedback score;

[0098] If the feedback score is greater than or equal to the satisfaction evaluation threshold, it indicates that the user is highly satisfied with the recommended content, and it is marked as satisfactory feedback;

[0099] If the feedback score is less than the satisfaction evaluation threshold, it indicates that the user is less satisfied with the recommended content and it is marked as unsatisfactory feedback.

[0100] As described in steps 1 to 2 above, first, a monitoring period is constructed. The purpose of this step is to count and analyze user feedback within a certain period of time. The monitoring period can be one day, one week, or one month, etc. The specific duration can be determined according to the needs of the platform and the user activity. During the monitoring period, the feedback scores of all users will be included in the statistical scope to ensure the comprehensiveness and accuracy of the results. Next, the satisfaction evaluation threshold is obtained. This threshold is a definition of user satisfaction. It can be determined based on historical data, expert opinions, or the platform's own experience. After obtaining the satisfaction evaluation threshold, it is necessary to compare it with the user's feedback score. Comparing the feedback score with the satisfaction evaluation threshold is to determine the user's satisfaction with the recommended content. If the feedback score is greater than or equal to the satisfaction evaluation threshold, it can be considered that the user is highly satisfied with the recommended content. In this case, such feedback can be marked as satisfactory feedback, indicating that the recommendation system has achieved good results in this recommendation. Conversely, if the feedback score is less than the satisfaction evaluation threshold, the user is less satisfied with the recommended content. In this case, such feedback is marked as unsatisfactory feedback, which means that the recommendation system has room for improvement in this recommendation.

[0101] In a preferred embodiment, the step of inputting the interactive response rate and the feedback satisfaction into the evaluation model to obtain the promotion score includes:

[0102] S401, obtaining an interactive response rate, and marking it as a first parameter to be evaluated;

[0103] S402, obtaining the percentage of satisfactory feedback and marking it as the second parameter to be evaluated;

[0104] S403, calling an evaluation function from the evaluation model, and inputting the first parameter to be evaluated and the second parameter to be evaluated into the evaluation function together, and marking the output result as the promotion score;

[0105] S404, calling an evaluation threshold from the evaluation model, and comparing the evaluation threshold with the promotion score;

[0106] If the promotion score is greater than or equal to the evaluation threshold, there is no need to optimize the website construction promotion content;

[0107] If the promotion score is less than the evaluation threshold, the website construction promotion content will be optimized.

[0108] As described in the above steps S401-S404, when the evaluation model is executed, the interaction response rate is first calibrated as the first parameter to be evaluated, and the proportion of satisfactory feedback in all feedback satisfaction is calibrated as the second parameter to be evaluated. After that, the evaluation function is called from the evaluation model, wherein the expression of the evaluation function is: P=a1f1+a2f2, wherein P represents the promotion score, a1 represents the weight factor of the first parameter to be evaluated, f1 represents the first parameter to be evaluated, a2 represents the weight factor of the second parameter to be evaluated, and f2 represents the second parameter to be evaluated. Based on the above formula, the promotion score of the recommended content in the interaction process can be directly output, and finally the promotion score is compared with the evaluation threshold to determine the effect of the website construction promotion, and when the promotion score is less than the evaluation threshold, the website construction promotion content is optimized to improve the user experience of the website, including interface design, page layout, loading speed and other aspects.

[0109] The present invention also provides a visualized website construction promotion system, which is applied to the above-mentioned visualized website construction promotion method, comprising:

[0110] The information collection module is used to obtain the user's access information, wherein the access information includes access duration, access times, access content and access target;

[0111] The recommendation module is used to perform classification extraction on the access content to obtain key access fields and non-key access fields, and then input the key access fields and non-key access fields into the pairing model to obtain recommended content;

[0112] Feedback module, which is used to obtain user feedback information on recommended content. The feedback information includes interactive response rate and feedback satisfaction, where feedback satisfaction includes satisfactory feedback and unsatisfactory feedback;

[0113] The evaluation module is used to input the interactive response rate and feedback satisfaction into the evaluation model to obtain the promotion score, and optimize the website construction promotion content according to the promotion score.

[0114] In the above, when the promotion system is executed, the information collection module is first used to collect the user's access information. This information includes but is not limited to the access time, number of visits, access content and access target. Through this information, the system can initially understand the user's interests and needs, and provide data support for the subsequent recommendation module. Then, the opinion module is used to classify and extract the access content, and distinguish the key access fields from the non-key access fields. Next, these fields will be input into the matching model. After the model operation, targeted recommended content is obtained. In this way, when the user browses the website, he can see more content that suits his interests, which improves the user experience. Then, the feedback module is used to collect the user's feedback on the recommended content. This Some feedback information includes interactive response rate and feedback satisfaction, among which feedback satisfaction can be further divided into satisfied feedback and dissatisfied feedback. Through these feedback information, the system can timely understand the changes in user needs and further optimize the recommended content. Finally, the evaluation module is used to evaluate the key part of the website construction and promotion effect. It takes the interactive response rate and feedback satisfaction into consideration and calculates the promotion score through the evaluation model. According to this score, the website can adjust the promotion strategy in a targeted manner to improve the quality and effect of website construction and promotion. The system forms a closed-loop optimization system, which can capture user access information and feedback in real time, and continuously adjust and optimize recommended content, thereby improving user satisfaction and achieving the goal of website construction and promotion.

[0115] And, a visual website construction promotion device, comprising:

[0116] at least one processor;

[0117] and a memory communicatively coupled to the at least one processor;

[0118] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the above-mentioned visualized website construction and promotion method.

[0119] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0120] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A visual website construction and promotion method, characterized by: include: Obtaining the user's access information, wherein the access information includes access duration, access times, access content, and access target; Performing classification extraction on the access content to obtain key access fields and non-key access fields, and then inputting the key access fields and non-key access fields into a pairing model to obtain recommended content; Acquiring user feedback information on the recommended content, the feedback information including an interactive response rate and feedback satisfaction, wherein the feedback satisfaction includes satisfactory feedback and unsatisfactory feedback; The interactive response rate and the feedback satisfaction are input into the evaluation model to obtain a promotion score, and the website construction promotion content is optimized according to the promotion score; The step of performing classification extraction on the access content to obtain key access fields and non-key access fields comprises: Acquire the access content, perform word segmentation processing on it, obtain multiple independent words, perform vector conversion on each of the independent words, obtain multiple numerical vectors, and mark them as parameters to be evaluated; Inputting the parameters to be evaluated into the evaluation model to obtain the correlation index of each parameter to be evaluated; Obtaining an evaluation threshold and comparing it with the correlation index; If the correlation index is greater than or equal to the evaluation threshold, the corresponding parameter to be evaluated is marked as a key access field; If the correlation index is less than the evaluation threshold, the corresponding parameter to be evaluated is marked as a non-critical access field; The step of inputting the parameters to be evaluated into the evaluation model to obtain the correlation index of each parameter to be evaluated includes: Obtaining all the parameters to be evaluated and the benchmark keywords under the access target; The evaluation function is called from the evaluation model, wherein the expression of the evaluation function is: , where represents the correlation index, represents the parameter to be evaluated, Represents the numerical vector corresponding to the benchmark keyword, represents the number of features in the parameters to be evaluated and the benchmark keywords, represents the parameter to be evaluated, Represents the mean of the numerical vector corresponding to the benchmark keyword; Inputting the parameter to be evaluated and the benchmark keyword into an evaluation function, and marking the output result as the correlation index of the parameter to be evaluated; The step of inputting the key access field and the non-key access field into the pairing model to obtain recommended content includes: Acquire the key access field and the non-key access field; Calling the response information corresponding to the access target from the pairing model, wherein the response information includes a response text, a response picture and a video; Acquire all response information corresponding to the key access field and the non-key access field, and perform response output according to the correlation index corresponding to each response information, and mark the output content as recommended content; The step of outputting a response according to the correlation index corresponding to each response information includes: Acquire all response information corresponding to the key access field and the non-key access field, wherein the same response information corresponds to several key access fields and non-key access fields; Summarize the correlation indexes of the key access fields and the non-key access fields in each of the response information to obtain a total correlation degree, and arrange the total correlation degrees from large to small according to their values, and then output the corresponding response information one by one in this order; The step of obtaining user feedback information on the recommended content includes: Get the user's access time in real time; Obtaining a standard duration and comparing it with the access duration, and generating a greeting statement when the access duration is greater than or equal to the standard duration; Counting the number of times the greeting statement is issued and the number of times the user responds, performing a combined operation, and marking the operation result as an interactive response rate; After the interaction is completed, a satisfaction rating list is generated, and user feedback ratings are counted based on the satisfaction rating list, and user satisfaction is determined based on the feedback ratings.

2. A visual website construction and promotion method according to claim 1, characterized in that: The step of determining user satisfaction based on the feedback score comprises: Construct a monitoring period and count the feedback scores of all users within the monitoring period; Obtaining a satisfaction evaluation threshold and comparing it with the feedback score; If the feedback score is greater than or equal to the satisfaction evaluation threshold, it indicates that the user is highly satisfied with the recommended content, and it is marked as satisfactory feedback; If the feedback score is less than the satisfaction evaluation threshold, it indicates that the user is less satisfied with the recommended content, and it is marked as unsatisfactory feedback.

3. A visual website construction and promotion method according to claim 1, characterized in that: The step of inputting the interactive response rate and the feedback satisfaction into the evaluation model to obtain the promotion score includes: Obtaining the interactive response rate, and marking it as a first parameter to be evaluated; Obtain the percentage of satisfactory feedback and mark it as the second parameter to be evaluated; Calling an evaluation function from the evaluation model, inputting the first parameter to be evaluated and the second parameter to be evaluated into the evaluation function, and marking the output result as a promotion score; Retrieving an evaluation threshold from the evaluation model, and comparing the evaluation threshold with the promotion score; If the promotion score is greater than or equal to the evaluation threshold, there is no need to optimize the website construction promotion content; If the promotion score is less than the evaluation threshold, the website construction promotion content is optimized.

4. A visual website construction and promotion system, applied to the visual website construction and promotion method according to any one of claims 1 to 3, characterized in that: include: An information collection module, the information collection module is used to obtain the user's access information, wherein the access information includes access duration, access times, access content and access target; A recommendation module, the recommendation module is used to perform classification extraction on the access content to obtain key access fields and non-key access fields, and then input the key access fields and non-key access fields into a pairing model to obtain recommended content; A feedback module, the feedback module is used to obtain user feedback information on the recommended content, the feedback information includes an interactive response rate and feedback satisfaction, wherein the feedback satisfaction includes satisfactory feedback and unsatisfactory feedback; An evaluation module is used to input the interactive response rate and feedback satisfaction into an evaluation model to obtain a promotion score, and optimize the website construction promotion content according to the promotion score.

5. A visual website construction and promotion device, characterized by: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the visualized website construction and promotion method described in any one of claims 1 to 3.

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