Fluid Topics offers each user a personalized search experience by mobilizing AI-powered natural language processing (NLP) that relies on content having metadata associated with it. Without metadata, content would not be easily searchable.
Fluid Topics makes a distinction between the following two types of metadata:
- Semantic metadata - Fluid Topics generates this metadata to manage content within the Knowledge Hub.
- Custom metadata - Content creators define this metadata to tag and classify content by author, version, product, platform, etc.
Examples of metadata in Fluid Topics
- Facets on the Homepage, Search page and Reader page allow users to refine their search.
- Tags in a document's Cover page identify the document's main categories at a glance.
- In some cases, Fluid Topics groups documents with the same tags together in a cluster.