Abstract: Representative embodiments disclose mechanisms to improve the perceived responsiveness of a search engine. As a user types a query prefix into a browser or other interface to the search engine, the search engine returns query completion suggestions to the browser. The query completion suggestions, user history, user favorites and/or other information are presented to a trained machine learning model on the client device to predict a desired location that the user is attempting to navigate to. When the confidence level of the predicted location surpasses a threshold, content from the desired location is preloaded into a hidden tab in the browser. When the user submits a query, the browser submits feedback to a system responsible for updating and refining the machine learning model. Updated machine learning model coefficients can be received by the browser from the system to make predictions more accurate.

Abstract: Representative embodiments disclose mechanisms to improve the perceived responsiveness of a search engine. As a user types a query prefix into a browser or other interface to the search engine, the search engine returns query completion suggestions to the browser. The query completion suggestions, user history, user favorites and/or other information are presented to a trained machine learning model on the client device to predict a desired location that the user is attempting to navigate to. When the confidence level of the predicted location surpasses a threshold, content from the desired location is preloaded into a hidden tab in the browser. When the user submits a query, the browser submits feedback to a system responsible for updating and refining the machine learning model. Updated machine learning model coefficients can be received by the browser from the system to make predictions more accurate.