Use Multiple Recommendation/Boosting Stages
Fusion provides three query-pipeline stages for content-based filtering and three query-pipeline stages for collaborative filtering. All of these stages recommend documents.
Examples of Using Multiple Collaborative Recommendation Stages
In some cases, using multiple recommendation stages in the query pipeline might make sense. The
<collection>_items_for_item_recommendations query pipelines are examples. In addition to a Recommend Items for User or Recommend Items for Item stages, each query pipeline also has a Boost with Signals stage. Thus, recommendations based on a Spark collaborative filtering computation are combined with recommendations based on the association of the query with items.
A Hybrid Recommender System
You can combine content-based filtering and collaborative filtering in the same query pipeline. A hybrid recommender system can leverage the capabilities and strengths of both approaches.