Patents by Inventor Max Edward Beech

Max Edward Beech has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • PERFORMANCE METRIC PREDICTION AND CONTENT ITEM TEXT SUGGESTION BASED UPON CONTENT ITEM TEXT
    Publication number: 20240168985
    Abstract: One or more computing devices, systems, and/or methods are provided. In an example, a first performance metric score may be determined based upon first content item text. A plurality of similarity scores associated with a plurality of sets of content item text may be determined. One or more sets of content item text may be selected from among the plurality of sets of content item text based upon the plurality of similarity scores and a plurality of performance metric scores associated with the plurality of sets of content item text. The plurality of performance metric scores may comprise one or more performance metric scores associated with the one or more sets of content item text. The one or more performance metric scores may be higher than the first performance metric score. One or more representations of the one or more sets of content item text may be displayed.
    Type: Application
    Filed: January 30, 2024
    Publication date: May 23, 2024
    Inventors: Shaunak Mishra, Changwei Hu, Kevin Yen, Manisha Verma, Yifan Hu, Maxim Ivanovich Sviridenko, Avinash Chukka, Max Edward Beech, Chao-Hung Wang, Hua-Ying Tsai, Kamil Michal Zasadzinski, Wei Yu Lin, Yu Tian
  • Performance metric prediction and content item text suggestion based upon content item text
    Patent number: 11886478
    Abstract: One or more computing devices, systems, and/or methods are provided. In an example, a first performance metric score may be determined based upon first content item text. A plurality of similarity scores associated with a plurality of sets of content item text may be determined. One or more sets of content item text may be selected from among the plurality of sets of content item text based upon the plurality of similarity scores and a plurality of performance metric scores associated with the plurality of sets of content item text. The plurality of performance metric scores may comprise one or more performance metric scores associated with the one or more sets of content item text. The one or more performance metric scores may be higher than the first performance metric score. One or more representations of the one or more sets of content item text may be displayed.
    Type: Grant
    Filed: May 7, 2021
    Date of Patent: January 30, 2024
    Assignee: Yahoo Assets LLC
    Inventors: Shaunak Mishra, Changwei Hu, Kevin Yen, Manisha Verma, Yifan Hu, Maxim Ivanovich Sviridenko, Avinash Chukka, Max Edward Beech, Chao-Hung Wang, Hua-Ying Tsai, Kamil Michal Zasadzinski, Wei Yu Lin, Yu Tian
  • PERFORMANCE METRIC PREDICTION AND CONTENT ITEM TEXT SUGGESTION BASED UPON CONTENT ITEM TEXT
    Publication number: 20220358153
    Abstract: One or more computing devices, systems, and/or methods are provided. In an example, a first performance metric score may be determined based upon first content item text. A plurality of similarity scores associated with a plurality of sets of content item text may be determined. One or more sets of content item text may be selected from among the plurality of sets of content item text based upon the plurality of similarity scores and a plurality of performance metric scores associated with the plurality of sets of content item text. The plurality of performance metric scores may comprise one or more performance metric scores associated with the one or more sets of content item text. The one or more performance metric scores may be higher than the first performance metric score. One or more representations of the one or more sets of content item text may be displayed.
    Type: Application
    Filed: May 7, 2021
    Publication date: November 10, 2022
    Inventors: Shaunak Mishra, Changwei Hu, Kevin Yen, Manisha Verma, Yifan Hu, Maxim Ivanovich Sviridenko, Avinash Chukka, Max Edward Beech, Chao-Hung Wang, Hua-Ying Tsai, Kamil Michal Zasadzinski, Wei Yu Lin, Yu Tian