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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Hauptverfasser: Baecke, Paul, Sheldon, David, Pradhan, Malik Mehdi, Hill, Daniel, Novielli, Nathan, Lyndersay, Sean, Zhong, Yan, Mehta, Dheeraj
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creator Baecke, Paul
Sheldon, David
Pradhan, Malik Mehdi
Hill, Daniel
Novielli, Nathan
Lyndersay, Sean
Zhong, Yan
Mehta, Dheeraj
description 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.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
title Machine learning model to preload search results
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