How do related document tags intelligently display content similar to the current article theme?

How to guide visitors to more related content naturally after they finish reading an article in content operation, which can not only significantly improve user experience but also effectively extend the visitors' stay on the website, reduce the bounce rate, and thus have a positive impact on search engine optimization (SEO).This AnQi CMS understands this well, it provides an intelligent and flexible mechanism that allows us to easily implement this 'You might also like' content recommendation.

The first step in building associations with content tags

The core of AnQi CMS's implementation of intelligent content association lies in its powerful 'tag' function.When editing articles in the background, we can add one or more tags to each article. These tags are like keywords or thematic categories of the content, but more flexible and detailed than traditional categories.

For example, an article discussing "website SEO optimization techniques" can be tagged with "SEOThese tags not only help us organize content, but more importantly, they build a bridge for the interconnection of content in the safety CMS.The system can "understand" the potential connections between different articles by analyzing these tags, laying the foundation for subsequent intelligent recommendations.

In the Aanqi CMS backend, adding tags to articles is a very intuitive process.In the "Publish DocumentThis convenient operation encourages us to set precise tags for each article, thereby building a rich and precise content association network.

The secret of intelligent recommendations:archiveListTagstype="related"mode

It is not enough to add tags for intelligent recommendation, the truly powerful place of Anqi CMS lies in how it transforms these tags into actual recommendation content. This is mainly achieved through its templates.archiveListTo implement labels, especially when we are usingtypeparameter settings"related".

When we use the template on the article detail page{% archiveList archives with type="related" %}This code, when executed, the safe CMS will default to selecting other articles with similar publication time and themes based on the current article's category for recommendation.This means that even without additional configuration, the system can provide a set of basic intelligent recommendations, which is very convenient for users who want to quickly build a website and have basic content association functions.

However, if we need to control the recommendation logic more finely, the Safe CMS also provides additionallikeParameters:

• Based on keyword intelligent matching:like="keywords"If you want the recommended content to focus more on the keywords of the article, you cantype="related"On the basis of, addlike="keywords"Parameter.At this point, the system will prioritize matching with other articles that highly align with the current article's keywords (especially the first keyword of the article).This is due to the built-in keyword library management function of Anqi CMS, which helps us standardize the use of keywords and ensure the accuracy of content recommendation.Through this method, an article about "AnQiCMS Installation Tutorial" can intelligently recommend strongly related articles such as "AnQiCMS Deployment Guide" or "AnQiCMS Multi-site Configuration

• English selected relevant recommendations:like="relation"For certain scenarios that require manual intervention and fine selection of related content, such as product page matching recommendations, AnQi CMS also provideslike="relation"Option.This means that when we edit articles in the background, we can manually specify which articles should be associated and recommended with this content.This way gives us complete customization capabilities for recommendations, ensuring that each recommendation conforms to our预设 operational strategy.

Display intelligent recommendations on the page

The process of displaying these intelligent recommendations to visitors is also very direct. Usually, we will list these recommendations using a concise loop at the bottom of the article detail page.

An example of a typical template code snippet might look like this:

<div class="related-articles">
    <h3>您可能也喜欢：</h3>
    <ul>
    {% archiveList relatedPosts with type="related" limit="5" %}
        {% for item in relatedPosts %}
        <li><a href="{{item.Link}}">{{item.Title}}</a></li>
        {% empty %}
        <li>暂无相关推荐文章。</li>
        {% endfor %}
    {% endarchiveList %}
    </ul>
</div>

Through this code, the system will automatically query and display 5 recommended contents related to the current article topic. If combined withlike="keywords"orlike="relation"Parameters, the recommended accuracy will be further improved.

If you still want to display all tags of the current article on the article detail page for easy user exploration, you can usetagListTags:

<div class="article-tags">
    <span>标签：</span>
    {% tagList currentTags %}
        {% for tag in currentTags %}
        <a href="{{tag.Link}}">{{tag.Title}}</a>
        {% endfor %}
    {% endtagList %}
</div>

Optimize content correlation, enhance website value

By flexibly using the tag function of Anqi CMS,archiveListTagstype="related"Pattern, our website not only provides visitors with a better browsing experience, but also achieves significant improvement in search engine optimization.A precise internal link structure helps search engine spiders better crawl and understand the website content, and high-quality, relevant content recommendations can effectively extend user time on site and reduce bounce rates, all of which are key factors in building a high-quality website and achieving higher search engine rankings.

The intelligent tag and related document recommendation feature of Anqi CMS provides a set of efficient and flexible tools for content operators. Whether relying on the system's default intelligent matching, or through keyword and manual selection