Leverage Machine Learning
- Machine Learning Overview
- Use Product Recommendations (PR)
- Use Dynamic Navigation Experience (DNE)
- Use Automatic Relevance Tuning (ART)
- Use Query Suggestions (QS)
- Use Event Recommendations (ER)
- Manage Models
- Custom Context
- User Profile
- Understanding User Stitching
Use Automatic Relevance Tuning (ART)
In short, the ART feature learns what search users seek and delivers it.
In more detail, ART analyzes user behavior patterns from many Coveo Usage Analytics (Coveo UA) search visit actions (e.g., query reformulation, clicked results, whether a support case was submitted) to understand which clicked results and content lead to successful outcomes, such as self-service success. It automatically adjusts future search results, so that the best-performing content always rises to the top.
ART excels with popular and ambiguous queries, in which users only enter one or two terms, as well as with paragraph-sized queries expressing long descriptions. ART can handle common typographical errors, and it learns implicit synonyms. When your Coveo index includes content from sources that index permissions, ART queries the index to ensure that it only recommends items that the user performing the query is allowed to access.
In practice, ART boosts the ranking weight of recommended items so that they appear among the top search results.
ART can also take advantage of the
PromotedResultsBadge component to highlight items that have been promoted in the results list.