Manage model associations with query pipelines

This is for:

Developer System Administrator

When a Coveo Machine Learning (Coveo ML) model has been created, it must be associated with a query pipeline to be effective in a search interface.

organization members with the required privileges can access the Machine learning tab of a query pipeline configuration page to manage Coveo ML model associations for that query pipeline.

Leading practices

Test the model efficiency

Once you’ve created a Coveo ML model, the leading practice is to test the model performance by doing an A/B test.

This allows you to test the model on a chosen proportion of the traffic passing through a given query pipeline. You can then assess the impact of the model by comparing the query pipeline search performance metrics with and without the model.

Once satisfied with the model efficiency, you can stop the A/B test to make the model effective for all the traffic passing through the query pipeline.

Validate that the model is effective

To validate that your Coveo ML models work as expected, you can inspect your models.

Plan the usage of custom contexts

While Coveo ML models can perform well without custom context information, using custom contexts can take Coveo ML relevance one step further.

You can define custom contexts and then pass appropriate ones along with Coveo Analytics events and queries to allow Coveo ML to take them into account.

Notes

  • Custom context support is limited under the new Event Protocol.

  • If you’re just getting started with Coveo ML, you can skip this step to take advantage of Coveo ML model types more quickly and easily, and consider using custom contexts in a second phase.

Associate a model with a query pipeline

How to associate a Coveo ML model with a query pipeline depends on the model type:

Dissociate a model

On the Machine learning tab of the desired query pipeline, click the model that you want to dissociate from this pipeline, and then click Dissociate in the Action bar.

Reorder model associations

The order in which models appear in the query pipeline Machine learning tab is only relevant when multiple models of the same type are present. If there are no duplicate model types in the list, the model order has no effect and each model will either execute or not based on its individual condition.

However, when multiple models of the same type are present, the models are evaluated sequentially from top to bottom. Depending on the model type, either only the first model with a satisfied condition is executed (and all subsequent models of the same type are ignored), or multiple models of the same type can be executed for the same query. See the documentation for your model type for details.

"Advanced Configuration" section

When association ART, DNE, and PR models with a query pipeline, the Administration Console lets you configure settings in the Advanced Configuration section. Click one of the following model links to access the corresponding procedure:

Required privileges

By default, members with the required privileges can view and edit elements of the Models (platform-ca | platform-eu | platform-au) page.

The following table indicates the privileges required to use elements of the Models page and associated panels (see Manage privileges and Privilege reference).

Action Service - Domain Required access level

View model associations

Machine Learning - Models
Organization - Organization
Search - Query pipelines

View

Edit model associations

Organization - Organization
Machine Learning - Models

View

Search - Query pipelines

Edit