NavBoost is a machine learning algorithm developed by Google to improve the relevance of search results based on user actions. By analyzing user interactions on Google Chrome, this algorithm aims to refine the ranking of web pages by taking into account user engagement and preferences.

To achieve this, NavBoost categorizes results based on parameters such as location, device type (mobile or desktop), and other contextual elements. This approach allows for the presentation of personalized results that precisely meet each user’s expectations.

By examining various user data, such as click-through rates (CTR), online behavior, website quality, and content relevance, the algorithm determines the most appropriate search results. By focusing on user intent, NavBoost prioritizes the most useful and relevant content in search results.