- Understanding Custom Context
- Leveraging Custom Contexts
- Understanding User Stitching
- Feature Selection
- Event Recommendations Deployment Overview
- Deploying Dynamic Navigation Experience
- Adding Coveo Machine Learning Blocklist Words
- About the PermanentId Field
Coveo Machine Learning Event Recommendations Deployment Overview
The output of a Coveo Machine Learning (Coveo ML) Event Recommendations (ER) model depends on the history of recent user actions and recorded Coveo Usage Analytics (Coveo UA) search, click, and view events (see Event Recommendations Feature).
More usage analytics data provides better recommendations, so you should start sending view events to Coveo UA as soon as possible (see How Long Do Coveo ML Features Take to Start Improving Relevance?).
Deploying Coveo ML ER requires programming skills.
In a technical documentation site, you could add a People Also Viewed recommendation interface to complement the table of contents and suggest articles which are frequently viewed by other users with similar session navigation history. Such an interface is rendered at the bottom of each article (including this one) on docs.coveo.com.
Deploying Coveo Machine Learning Event Recommendations (ER)
Optionally, plan the types of content to recommend:
A Coveo ML ER model can be configured to learn only from usage analytics events pertaining to one or several specific types of content. Therefore, unless you want to create a model that outputs generic recommendations, you should plan ahead.
You want to design a Recommended Articles interface, and a Recommended Courses interface.
You determine that the Recommended Articles interface should only take the
KBArticlecontent type into account, whereas the Recommended Courses interface should take the
InteractiveTutorialcontent types into account.
You can determine what contextual user information is relevant to your use-case, and send this data along with each usage analytics event and query to allow your Coveo ML Event Recommendations model to further personalize its output (see Leveraging Custom Contexts in Coveo Machine Learning Features).
You want the output of your recommendation interfaces to be tailored to the products owned by the end user.
You determine that you should leverage this contextual user information.
You need an access token granting limited privileges to:
Allow tracked pages to send usage analytics view events in order to feed your ER models.
Allow your recommendation interfaces to send queries to get recommendations, and send usage analytics search and click events for reporting purposes (see Include a recommendation interface in a web page).
Depending on your use case, you can use either:
A search token.
Send usage analytics events:
Send view events.
As soon as possible, use the
coveoua.jsscript to start recording usage analytics view events in the web pages which correspond to the indexed items you want to be able to recommend (see Sending Usage Analytics View Events).
Send search and click events.
Coveo ML ER models can also learn from search and click events originating from other search interfaces configured against the same Coveo organization. Ensure that all of your search pages are properly configured to send standard usage analytics events (see Getting Started With Coveo Usage Analytics).
Use a query pipeline dedicated to ER models to ensure that other search optimization features, such as Coveo ML Automatic Relevance Tuning (ART) or query ranking expressions (QRE), don’t interfere with the output of the ER models.
When you want to power distinct recommendation interfaces (e.g., Recommended Technical Articles, Recommended Experts, Recommended Courses, etc.), configure a separate model for each planned interface. Associate them all with the same ER-dedicated query pipeline and add a specific condition to each model.
Don’t use the Default query pipeline for your ER model. Otherwise, all search interfaces routing their queries to the Default pipeline will essentially break.
Recommendationcomponent that you can configure in your web pages to create one or more recommendation interfaces (see Integrating a Coveo Recommendation Interface in a Web Page).
For a Recommendations widget in a ServiceNow service portal, see Configuring a Recommendations Panel.
You may now want to have a look at an actual code sample to consolidate your understanding of the Coveo ML ER deployment process in a website.