Thanks to Sherpa.ai’s general purpose technology, you can create recommendations using your catalog content (your products and services), such as movies, music, news, books, or clothes, and build ad hoc product and service recommendations, by following these steps:
- Step 1: Build your Item Catalog (General Purpose): Organize your items in tables; they can have any number of attributes.
- Step 2: Create your User Profile: Organize your users in tables; they can have any number of attributes. The attributes are used for modeling users.
- Step 3: Register your Item-Client interactions and parametrize your business rules; select a method to manage the interactions that occur between your users and items.
Step 4: Make and Filter Recommendations:
- Recommend items that are most likely to be of great value for a given user (Item to User)
- Get users that are similar to another user (User to User)
- Recommend a set of items that are somehow related to one given item (Item to Item)
- Recommend users that are likely to be interested in a given item (Users to Item)
The Sherpa.ai Custom Content Recommendation API is a REST API that provides developers with a framework and toolbox to formulate any request for Sherpa.ai, by using standard syntax technologies like HTTP Rest Services with a predefined set of URLs.
An interactive tutorial based on Jupyter Notebooks is also available: