INTELLIGENT SNAP ASSIST RECOMMENDATION MODEL

The techniques disclosed herein enable systems to provide intelligent snap assist recommendations using a diverse set of factors and factor weights. To generate recommendations, a system receives a user input placing a first item in a region of a snapped configuration in a display environment. In response, the system assigns a confidence score for a plurality of items including items open in the display environment as well as items that are not open. The system then ranks the items based on confidence score and selects a list of recommended items from the ranked list. The recommended items are then presented in a second region of the snapped configuration for selection. The system is further configured to receive and analyze user selections of snapped items to learn over time and adjust confidence scoring.