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Tags represent individual topics of expertise.
Starmind implements advanced natural language processing algorithms that can identify the most relevant tags (topics of expertise) in any document.
Automatic tagging endpoints
Starmind offers different endpoints for automatic tagging (also known as keyphrase extraction).
For example, from the input "What is the difference between penne and macaroni?", these endpoints might return the tags "penne", "macaroni" and "pasta".
The automatic tagging endpoints have a parameter to configure the tag behaviour for specific input types.
POST api/v1/tags/extract (API docs)
Tag extraction endpoint extracts tags from a given text, independently of the tags that are already in the network.
This endpoint can be applied to any type of text that might contain topics of expertise, for example a chat message, a project description, etc.
POST api/v1/search/tags/suggestions (API docs)
Tag suggestion endpoint returns suggested tags for a given title/description combination. It is optimised to obtain good tags for questions, helping the expert search to identify the best experts when the question is published.
GET /api/v1/search/tags (API docs)
Tag search finds tags based on a short search query. For example, from the query "Star", the tags "Starmind" and "Star Wars" could be returned.