Abstract: Methods and systems described herein may improve search results for items newly added to a database by using machine learning to map historical items in the database to the newly added items. For example, non-conventional methods and systems described herein may use machine learning generated embeddings (e.g., vector representations of items) to determine the extent to which two items are similar to each other. The computing system may assign engagement data associated with a first item to a second item that lacks engagement data. By doing so, the computing system may enable improved search results because the position of items that lack engagement data (e.g., newly added items) may be adjusted based on engagement data associated with similar items.

Abstract: A tandem tricycle having a front frame portion and a detachable rear frame portion, which is configured to accommodate two riders. A drivetrain allows the riders to independently power the tricycle. A full suspension assembly provides a smoother ride.