How are content recommendations and related topics implemented in manufacturing documentation portals with DITA?

Implementing content recommendations and related topics in manufacturing documentation portals with DITA XML can significantly enhance user experience and knowledge discovery. These features help users find relevant information more efficiently, promoting better comprehension of manufacturing processes and products.

Related Topics

DITA enables the establishment of relationships between topics, allowing for the creation of “related topics” sections. In manufacturing documentation, this feature can be used to link topics that share context or dependencies. For example, a topic on “Product Assembly” can have related topics such as “Materials List” and “Quality Control Procedures.” Users can easily navigate to these related topics to gain a comprehensive understanding of the assembly process.

Content Recommendations

Manufacturing documentation portals can leverage content recommendation engines to suggest related topics to users. These recommendations are based on user behavior, search queries, or predefined rules. For instance, if a user is reading a topic on “Troubleshooting,” the portal can recommend related topics like “Common Error Codes” or “Maintenance Procedures.” DITA XML supports the implementation of these recommendation systems, enhancing the user’s ability to discover valuable content.


Here’s an example of how DITA XML facilitates the implementation of related topics and content recommendations in manufacturing documentation:

<topic id="product_assembly">
  <title>Product Assembly</title>
    <topic-ref href="materials_list.dita">Materials List</topic-ref>
    <topic-ref href="quality_control.dita">Quality Control Procedures</topic-ref>

In this example, a DITA topic on “Product Assembly” includes related topics (“Materials List” and “Quality Control Procedures”) as references, allowing users to easily access relevant content. Additionally, content recommendation engines can be integrated into the portal to suggest these related topics based on user interactions.