Machine learning model to preload search results

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, u...

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Bibliographische Detailangaben
Hauptverfasser: Baecke, Paul, Sheldon, David, Pradhan, Malik Mehdi, Hill, Daniel, Novielli, Nathan, Lyndersay, Sean, Zhong, Yan, Mehta, Dheeraj
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung: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.