The document discusses the creation of PebbleAppTailor, a tool for recommending Pebble apps to users. It aims to increase user engagement by predicting app usage based on a user's existing apps and launch counts. It uses item-based collaborative filtering and cosine similarity matrix calculations on a sparse dataset. The recommendations are validated using a leave-one-out method to test if removed apps can be correctly suggested. Next steps include categorizing apps using NLP and highlighting categories that leverage the Pebble hardware's uniqueness.