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This capsule discusses how to use preference learning.
Preference learning is done offline and is not currently demonstrated in the Simulator. This capsule primarily shows what full modeling for preference learning might look like.
There are two primary capabilities modeled in this capsule: a search functionality for flowers (
FindFlowers) and a search functionality for flights (
This functionality demonstrates how to use bootstrap preferences, which is primarily set up through the
ProductType.preference.bxb file. When returning
FlowerProduct structures, it lists
FlowerArrangement types first for users to choose from, as users typically look for these arrangements. Additionally, as the user continues to make choices when searching for flowers, eventually Bixby will learn the
productTypes and flower types (through the
name property) that the user prefers.
This functionality demonstrates how to use
observation-alias. When a user selects an airline's logo from the given results, the
Carrier.code property is marked as a preferred option by the user. While the
logo cannot be a
preferable property of the
Trip because it is an image, it can be associated with a property that can be considered preferable.