- 专利标题: Machine learning model to preload search results
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申请号: US15919065申请日: 2018-03-12
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公开(公告)号: US10754912B2公开(公告)日: 2020-08-25
- 发明人: Nathan Novielli , Yan Zhong , Paul Baecke , Sean Lyndersay , David Sheldon , Malik Mehdi Pradhan , Dheeraj Mehta , Daniel Hill
- 申请人: Microsoft Technology Licensing, LLC
- 申请人地址: US WA Redmond
- 专利权人: Microsoft Technology Licensing, LLC
- 当前专利权人: Microsoft Technology Licensing, LLC
- 当前专利权人地址: US WA Redmond
- 代理机构: Medley, Behrens & Lewis, LLC
- 主分类号: G06F17/00
- IPC分类号: G06F17/00 ; G06F16/957 ; G06N20/00 ; G06F16/951 ; G06F16/955 ; G06F16/2457
摘要:
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.
公开/授权文献
- US20190278870A1 MACHINE LEARNING MODEL TO PRELOAD SEARCH RESULTS 公开/授权日:2019-09-12
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