SEO automatic setting system and method in station building CMS

Abstract

The invention provides an automatic SEO setting system and method in a station building CMS, and belongs to the technical field of station building CMS. According to the method, the AI technology is utilized, the keywords are deeply mined and screened, the keywords with high conversion potential and the long tail keywords are accurately recognized, the real demands of users are insighted, the competition situation of the keywords is intelligently evaluated, and the popularity change is predicted. In the aspect of content creation, a content outline, a first draft and a specific paragraph can be generated according to a target keyword and a user portrait, optimization suggestions can be provided in the aspects of readability, keyword layout and the like, and content personalized recommendation is achieved. Compared with a traditional SEO technology, the method has the advantages that the keyword screening efficiency and the long tail keyword coverage rate are improved, the matching degree of content and user requirements is optimized, ranking and flow of websites in a search engine are improved, and the method is efficient and accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of website building CMS, and in particular to a SEO automatic setting system and method in a website building CMS. Background Art

[0002] In today's digital age, websites have become crucial platforms for businesses, organizations, and individuals to showcase their image and disseminate information. As a core tool for website construction and management, content management systems (CMS) provide users with convenient content creation, publishing, and management capabilities. However, traditional CMS systems have several limitations. Traditional CMS systems rely on manual work for content creation, publishing, updating, and optimization, which not only consumes significant manpower and time, but also hinders efficient and continuous content output. Regarding content management efficiency, the classification, tagging, searching, and optimization of large amounts of content require significant effort, resulting in high management costs. Furthermore, traditional CMS systems struggle to provide accurate recommendations and customized services tailored to the needs of individual users, failing to meet their increasingly diverse demands.

[0003] With the rapid development of artificial intelligence (AI), particularly advancements in natural language processing (NLP), machine learning (ML), and deep learning (DL), AI is finding increasing application across various fields. In the realm of content creation, AI can automatically generate articles, images, videos, and other content based on a given theme, style, and requirements, offering new insights and methods for overcoming the limitations of traditional CMS systems. Furthermore, AI can enhance the user experience by providing more personalized services through intelligent recommendations and data analysis.

[0004] Search engine optimization (SEO) is a key technology for improving website rankings and increasing website traffic. By optimizing a website's content, structure, and links, it aligns with search engine algorithms, thereby increasing its visibility in search results. In the fiercely competitive online landscape, effective SEO strategies can help a website attract more potential users and enhance its visibility and influence. However, traditional SEO optimization requires specialized knowledge and experience, is labor-intensive, and inefficient, making it difficult to meet rapidly changing market demands. Summary of the Invention

[0005] The present invention aims to address the technical defects of the existing technology and provide a system and method for automatically setting SEO in a website building CMS to solve the technical problems that traditional SEO technology requires high professional knowledge and experience, and has a large workload and low efficiency.

[0006] Another technical problem to be solved by the present invention is that it is difficult for traditional CMS to achieve efficient and continuous content output.

[0007] In order to achieve the above technical objectives, the present invention adopts the following technical solutions: A website building CMS system, including: keyword map construction module, content generation module, SEO optimization module, traffic analysis module, and evaluation optimization module; The keyword graph construction module is used to analyze search data, user behavior data and competitor content using natural language processing and machine learning technologies to construct a dynamically updated keyword graph; The content generation module is used to automatically generate content containing matching SEO keywords based on the product or business theme input by the user and the keyword map using the AI ​​big model; The SEO optimization module is used to perform SEO optimization on the generated content; The traffic analysis module is used to monitor rankings and analyze traffic of SEO-optimized content, identify high-potential keywords and traffic conversion paths, and formulate traffic strategies. The evaluation and optimization module is used to evaluate and optimize the generated content and traffic delivery effects, and adjust the keyword map, AI model parameters and traffic delivery strategy based on the evaluation results.

[0008] Preferably, the content generated by the content generation module includes product descriptions, articles, images and videos; the SEO optimization includes adjusting keyword layout, optimizing content structure, setting internal links and page elements.

[0009] On the basis of the above technical solutions, the present invention further provides an AI automatic generation, SEO keyword matching and traffic acquisition method based on the above website building CMS system, comprising the following steps: 1) Leveraging natural language processing and machine learning technologies to analyze search data, user behavior data, and competitor content to build a dynamically updated keyword graph; 2) Based on the product or business theme entered by the user and combined with the keyword graph, the AI ​​model is used to automatically generate content containing matching SEO keywords; 3) SEO optimization of generated content; 4) Through ranking monitoring and traffic analysis of SEO-optimized content, we can identify high-potential keywords and traffic conversion paths, formulate traffic investment strategies, and push content to potential target users.

[0010] Preferably, the content generated in step 2) includes product descriptions, articles, images and videos; and the SEO optimization in step 3) includes adjusting keyword layout, optimizing content structure, setting internal links and page elements.

[0011] Preferably, the following step 5) is also included): the generated content and traffic effect are evaluated and optimized, and the keyword map, AI large model parameters and traffic strategy are adjusted according to the evaluation results; and then steps 1) to 4) are re-executed.

[0012] Preferably, step 1) includes: parsing user search intent through natural language processing technology to identify synonyms, long-tail variants, and potential related word groups of keywords; based on a machine learning model, quantitatively evaluating the search volume, competitiveness, commercial value, and conversion rate of keywords to generate a keyword value evaluation matrix; and monitoring search engine algorithm updates, changes in user search behavior, and adjustments to competitor keyword strategies in real time to dynamically adjust the keyword map.

[0013] Preferably, step 2) includes: using a keyword extraction algorithm based on a pre-trained model to extract keywords related to the topic from the keyword map; using the extracted keywords and other information input by the user as input, and using an AI large model to generate content, considering the semantic relevance and contextual consistency of the keywords during the generation process (to ensure the natural flow and logical coherence of the content); intelligently rewriting and optimizing the generated content (to further improve the originality and readability of the content); the optional range of the pre-trained model includes BERT and Deepseek.

[0014] Preferably, step 3) includes: optimizing the density, distribution, and position of keywords in the content (ensuring the rational use of keywords) based on the keyword map and search engine algorithm rules; optimizing the title, description, body structure, and format of the content (improving the readability and search engine friendliness of the content); setting internal and external links (enhancing the relevance and weight transfer between pages); and optimizing the technical indicators of the page, including loading speed, mobile adaptability, and security.

[0015] Preferably, the step 4) of determining high-potential keywords and traffic conversion paths includes: identifying high-potential keywords and traffic entrances by analyzing data on content in search engines, including ranking changes, traffic sources, user residence time, and conversion rates; using machine learning models to predict the traffic conversion potential of keywords, and adjusting keyword strategies and content optimization directions based on the prediction results; analyzing user behavior trajectories and conversion paths on the website, and optimizing page layout and content presentation (to improve user conversion rates).

[0016] Preferably, the step 4) of formulating a traffic delivery strategy includes: determining the characteristics and needs of the target user group based on high-potential keywords and traffic conversion paths; selecting traffic delivery channels and platforms; formulating a traffic delivery plan based on the characteristics of the target user group and the characteristics of the traffic delivery channels; monitoring the traffic delivery effect in real time, and adjusting the traffic delivery strategy based on traffic delivery data and user feedback; the traffic delivery channels and platforms include search engine advertising, social media advertising, and content marketing platforms; and the traffic delivery plan includes delivery time, delivery frequency, delivery budget, and delivery content.

[0017] Preferably, step 5) includes: establishing a content evaluation index system to regularly evaluate the generated content; adjusting and optimizing the parameters and keyword map of the AI ​​large model based on the content evaluation results (to improve the quality and accuracy of content generation); establishing a traffic injection effect evaluation index system to regularly evaluate the traffic injection effect; adjusting and optimizing the traffic injection strategy based on the traffic injection effect evaluation results (to improve the efficiency and effectiveness of traffic injection); the content evaluation index system includes the originality, readability, relevance, search engine ranking and traffic conversion rate of the content; the evaluation index system includes the exposure, click-through rate, conversion rate and input-output ratio of the traffic injection.

[0018] The present invention provides a system and method for automatically setting SEO in a website building CMS. As a technology that uses AI to automatically generate product and content SEO in a website building CMS system, the present invention uses AI technology to deeply mine and screen keywords, accurately identify high-conversion potential keywords and long-tail keywords, gain insight into users' real needs, and intelligently evaluate keyword competition situations and predict changes in popularity. In content creation, content outlines, drafts, and specific paragraphs can be generated based on target keywords and user portraits. Optimization suggestions can also be provided in terms of readability, keyword layout, and other aspects to achieve personalized content recommendations. Compared with traditional SEO technology, the present invention improves keyword screening efficiency and long-tail keyword coverage, optimizes the matching degree between content and user needs, and improves the website's ranking and traffic in search engines, with the advantages of high efficiency and accuracy.

[0019] Compared with the prior art, the beneficial effects of the present invention are also concentrated in the following aspects: 1. Improving content creation efficiency Traditional content creation requires a lot of manual work such as data collection, organization, and writing, which consumes a lot of time and energy. However, the system of the present invention uses AI technology to automatically generate content, which can generate a large amount of high-quality content in a short period of time, greatly improving the efficiency of content creation.

[0020] (2) Improving content quality and originality The AI content generation module can generate articles with unique expressions and innovative ideas by learning and analyzing massive amounts of data in combination with different keywords, themes, and styles. At the same time, the system also has the function of intelligent rewriting and optimization, which can recombine and polish existing articles to further improve the originality of the articles, help websites avoid content homogenization, and enhance the attractiveness and credibility of the website. In some actual tests, the AI-generated articles after filtering word control and model training have detection scores comparable to manually written content, and even have better semantic clarity and logical structure.

[0021] (Three) Realize SEO intelligent optimization The system of the present application combines AI technology with SEO optimization strategies, can automatically analyze the effect of keywords, provide suggestions for keyword optimization, and adjust the structure and format of the content to improve the ranking of the content in search engines. The system can also monitor the ranking changes of keywords in major search engines in real time, and adjust the SEO strategy in time according to the monitoring results to ensure that the ranking of the website always remains in a good position. Compared with traditional SEO optimization work, the system is more intelligent and efficient, and can save a lot of time and effort.

[0022] (Four) Provide personalized services The system can generate highly personalized content according to the specific needs of users (such as target audience, industry characteristics) to meet the content needs in different scenarios. In the user interaction module, users can set the parameters and requirements of content generation according to their own preferences, such as theme, style, language, etc., and the system will generate content that meets the user's needs according to the user's settings. At the same time, the system can continuously optimize the effect of content generation and SEO optimization according to user feedback to provide more personalized services for users.

[0023] (Five) Reduce costs For some small and medium-sized websites or individual webmasters, hiring a professional editing team to create content and optimize SEO often costs a lot. The system of the present application does not require additional human resources, only needs simple operation and setting to realize automatic generation of content and intelligent optimization of SEO, greatly reducing the cost of human resources. At the same time, the system can also improve the operation efficiency and benefit of the website, and bring more benefits to the users. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 is a flowchart of the method of the present application. DETAILED DESCRIPTION

[0025] The specific embodiments of the present application will be described in detail below. In order to avoid too many unnecessary details, the structure or function belonging to the known will not be described in detail in the following examples. The approximate language used in the following examples can be used for quantitative expression, indicating that the amount can be allowed to have certain changes without changing the basic function. Unless defined, the technical and scientific terms used in the following examples have the same meaning as generally understood by those skilled in the art to which the present application belongs.

[0026] (I) System architecture The website building CMS system of the present application combines AI technology and SEO optimization strategy, aiming to realize the automatic generation of products and content and the intelligent optimization of SEO. The system mainly consists of the following modules: 1. AI content generation module: This module is one of the cores of the system, based on advanced AI large models such as company internal models or other open source large models, can generate high-quality product description, article, image and video content according to the user input of keywords, theme, style and requirements. When generating articles, the system will consider the distribution of keywords, the coherence of semantics and the rationality of logic to ensure that the generated content meets the requirements of SEO. At the same time, this module also has the function of creative expansion and suggestion, which can provide more creative ideas and ideas according to the user input content, helping users to enrich the content.

[0027] 2. SEO optimization module: This module is responsible for the SEO optimization of the generated content. It will automatically analyze the effect of keywords, including the competitiveness, search volume and relevance of keywords, etc., to provide suggestions for keyword selection and optimization for users. During the content generation process, this module will automatically adjust the structure and format of the content, such as using appropriate header tags (H1, H2, etc.), internal link construction and picture ALT tag settings, etc., to improve the ranking of the content in search engines. In addition, this module can also monitor the ranking changes of keywords in major search engines in real time, provide detailed ranking reports and trend analysis for users, and adjust the SEO strategy in time according to the analysis results.

[0028] 3. Content management module: This module is used to manage the generated content, including content storage, classification, tagging and retrieval functions. Users can easily edit, modify and delete the content, and also can set the release time and permissions of the content. This module also supports the management of multi-language content, which can generate different language versions of content according to the user's needs.

[0029] 4. User Interaction Module: This module provides a user-friendly interface, allowing users to enter keywords, set content generation parameters and requirements, and view generated content and SEO optimization reports. This module also allows users to provide feedback and review generated content. The system continuously optimizes content generation and SEO optimization based on user feedback.

[0030] (2) Workflow 1. Keyword input: Users enter keywords related to products or content in the system's interactive interface. They can also set parameters such as the theme, style, language, and word count of the content to be generated.

[0031] 2. AI Content Generation: The AI ​​content generation module uses a large AI model to generate relevant content based on user-entered keywords and parameters. During the generation process, the system automatically considers SEO requirements, such as keyword density, distribution, and semantic relevance.

[0032] 3. SEO Optimization: The SEO Optimization module further optimizes the generated content. It analyzes keyword performance, provides keyword optimization suggestions, and adjusts the structure and format of the content to improve its ranking in search engines.

[0033] 4. Content Review and Publishing: Generated content will be displayed to users, who can review and modify it. Once approved, users can choose to publish the content to a designated website or platform.

[0034] 5. SEO monitoring and adjustment: The system will monitor the ranking changes of keywords in major search engines in real time, and adjust the SEO strategy according to the monitoring results to ensure that the website's ranking always remains in a good position.

[0035] The working principle of this embodiment is as follows: 1. Implementation of AI content generation 1. Data collection and preprocessing: Collect a large amount of text data related to products and content, including news articles and product descriptions. Perform preprocessing on this data, such as cleaning, word segmentation, and annotation, to improve data quality and usability.

[0036] 2. Model training: Select an appropriate large AI model, such as the GPT series model or an internal company model, and train the model using preprocessed data. During training, adjust the model parameters to improve the quality and accuracy of the content generated by the model.

[0037] 3. Content Generation: After the user enters keywords and parameters, the system feeds these into a trained model, which then generates relevant content based on the input. During the generation process, the system can adjust and optimize the content based on user requirements, such as controlling the length, style, and language of the content.

[0038] (2) Implementation of SEO optimization 1. Keyword research: Use keyword research tools like Google Keyword Planner and Ahrefs to analyze keyword competition, search volume, and relevance. Based on this analysis, select appropriate keywords as your target keywords and develop a corresponding SEO strategy for each keyword.

[0039] 2. Content Optimization: During content creation, target keywords should be strategically placed throughout the title, description, and body of the content to improve search engine rankings. Also, optimize the structure and format of the content, such as using appropriate title tags (H1, H2, etc.), building internal links, and setting image ALT tags.

[0040] 3. External link building: Increase the website's external links and improve the website's authority and search engine ranking by publishing high-quality content, exchanging links with industry-related websites, participating in industry reviews, etc.

[0041] 4. Technical Optimization: Focus on ensuring website loading speed, mobile compatibility, HTTPS encryption, XML sitemaps, and robots.txt files. These optimization measures can improve search engine crawling efficiency and user experience, thereby boosting your website's search rankings.

[0042] (3) System integration and deployment 1. System Integration: Integrate the AI ​​content generation module, SEO optimization module, content management module, and user interaction module to ensure that each module can work together. During the integration process, it is necessary to consider the interface and data transmission issues between modules to ensure system stability and reliability.

[0043] 2. System Deployment: Deploy the integrated system to a server, typically a cloud server. During the deployment process, you'll need to configure and test the system to ensure proper operation. Additionally, you'll need to implement security measures to prevent attacks and data leaks.

[0044] The embodiments of the present invention are described in detail above, but the contents are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the scope of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A website building CMS system, characterized in that: include: Keyword graph construction module, content generation module, SEO optimization module, traffic analysis module, and evaluation optimization module; The keyword graph construction module is used to analyze search data, user behavior data and competitor content using natural language processing and machine learning technologies to construct a dynamically updated keyword graph; The content generation module is used to automatically generate content containing matching SEO keywords based on the product or business theme input by the user and the keyword map using the AI ​​big model; The SEO optimization module is used to perform SEO optimization on the generated content; The traffic analysis module is used to monitor rankings and analyze traffic of SEO-optimized content, identify high-potential keywords and traffic conversion paths, and formulate traffic strategies. The evaluation and optimization module is used to evaluate and optimize the generated content and traffic delivery effects, and adjust the keyword map, AI model parameters and traffic delivery strategy based on the evaluation results.

2. A website building CMS system according to claim 1, characterized in that: The content generated by the content generation module includes product descriptions, articles, images and videos; the SEO optimization includes adjusting keyword layout, optimizing content structure, setting internal links and page elements.

3. The method for automatic AI generation, SEO keyword matching and traffic acquisition based on the website building CMS system of claim 1 is characterized in that: The following steps are involved: 1) Leveraging natural language processing and machine learning technologies to analyze search data, user behavior data, and competitor content to build a dynamically updated keyword graph; 2) Based on the product or business theme entered by the user and combined with the keyword graph, the AI ​​model is used to automatically generate content containing matching SEO keywords; 3) SEO optimization of generated content; 4) Through ranking monitoring and traffic analysis of SEO-optimized content, we can identify high-potential keywords and traffic conversion paths, formulate traffic investment strategies, and push content to potential target users.

4. The method according to claim 3, characterized in that The following step 5) is also included): Evaluate and optimize the generated content and traffic delivery effects, adjust the keyword map, AI model parameters and traffic delivery strategy based on the evaluation results; and then re-execute steps 1) to 4).

5. The method according to claim 3, characterized in that Step 1) includes: parsing user search intent through natural language processing technology to identify synonyms, long-tail variants, and potential related word groups of keywords; based on machine learning models, quantitatively evaluating the search volume, competitiveness, commercial value, and conversion rate of keywords to generate a keyword value assessment matrix; and dynamically adjusting the keyword map by monitoring search engine algorithm updates, changes in user search behavior, and adjustments to competitor keyword strategies in real time.

6. The method according to claim 3, characterized in that Step 2) includes: using a keyword extraction algorithm based on a pre-trained model to extract keywords related to the topic from the keyword map; using the extracted keywords and other information entered by the user as input, using an AI large model to generate content, considering the semantic relevance and contextual consistency of the keywords during the generation process; and intelligently rewriting and optimizing the generated content. The optional range of pre-trained models includes BERT and Deepseek.

7. The method according to claim 3, characterized in that Step 3) includes: optimizing keyword density, distribution, and placement within the content based on keyword graphs and search engine algorithms; optimizing the title, description, and body structure and format of the content; setting internal and external links; and optimizing the page's technical indicators, including loading speed, mobile compatibility, and security.

8. The method according to claim 3, characterized in that Determining high-potential keywords and traffic conversion paths as described in step 4) includes: identifying high-potential keywords and traffic entrances by analyzing data on content in search engines, including ranking changes, traffic sources, user dwell time, and conversion rates; using machine learning models to predict the traffic conversion potential of keywords, and adjusting keyword strategies and content optimization directions based on the prediction results; analyzing user behavior trajectories and conversion paths on the website, and optimizing page layout and content presentation.

9. The method according to claim 3, characterized in that Step 4) involves formulating a traffic strategy, including: determining the characteristics and needs of the target user group based on high-potential keywords and traffic conversion paths; selecting traffic channels and platforms; formulating a traffic plan based on the characteristics of the target user group and the characteristics of the traffic channels; monitoring traffic effectiveness in real time, and adjusting the traffic strategy based on traffic data and user feedback; the traffic channels and platforms include search engine advertising, social media advertising, and content marketing platforms; and the traffic plan includes delivery time, delivery frequency, delivery budget, and delivery content.

10. The method according to claim 4, characterized in that Step 5) includes: establishing a content evaluation index system to regularly evaluate the generated content; adjusting and optimizing the parameters and keyword maps of the AI ​​model based on the content evaluation results; establishing a traffic injection effect evaluation index system to regularly evaluate the traffic injection effect; adjusting and optimizing the traffic injection strategy based on the traffic injection effect evaluation results; the content evaluation index system includes the originality, readability, relevance, search engine ranking and traffic conversion rate of the content; the evaluation index system includes the exposure, click-through rate, conversion rate and input-output ratio of the traffic injection.

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