Patents by Inventor Alexander Shtoff

Alexander Shtoff 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).

  • Patent number: 11868228
    Abstract: In an example, sets of event information associated with events may be identified. The events may include intentional click events, accidental click events and/or skip events. Accidental click probabilities associated with the accidental click events and/or the skip events may be determined. Machine learning model training may be performed, using the sets of event information associated with the events and labels associated with the events, to generate a first machine learning model. The labels may include second labels associated with the intentional click events and/or third labels associated with the accidental click events and/or the skip events. The second labels may correspond to an intentional click classification. The third labels may be based upon the accidental click probabilities. Click probabilities associated with content items may be determined using the first machine learning model. A content item may be selected for presentation via a client device based upon the click probabilities.
    Type: Grant
    Filed: January 19, 2023
    Date of Patent: January 9, 2024
    Assignee: Yahoo Ad Tech LLC
    Inventors: Naama Haramaty-Krasne, Yohay Kaplan, Oren Shlomo Somekh, Alexander Shtoff
  • Publication number: 20230153221
    Abstract: In an example, sets of event information associated with events may be identified. The events may include intentional click events, accidental click events and/or skip events. Accidental click probabilities associated with the accidental click events and/or the skip events may be determined. Machine learning model training may be performed, using the sets of event information associated with the events and labels associated with the events, to generate a first machine learning model. The labels may include second labels associated with the intentional click events and/or third labels associated with the accidental click events and/or the skip events. The second labels may correspond to an intentional click classification. The third labels may be based upon the accidental click probabilities. Click probabilities associated with content items may be determined using the first machine learning model. A content item may be selected for presentation via a client device based upon the click probabilities.
    Type: Application
    Filed: January 19, 2023
    Publication date: May 18, 2023
    Inventors: Naama Haramaty-Krasne, Yohay Kaplan, Oren Shlomo Somekh, Alexander Shtoff
  • Patent number: 11561879
    Abstract: In an example, sets of event information associated with events may be identified. The events may include intentional click events, accidental click events and/or skip events. Accidental click probabilities associated with the accidental click events and/or the skip events may be determined. Machine learning model training may be performed, using the sets of event information associated with the events and labels associated with the events, to generate a first machine learning model. The labels may include second labels associated with the intentional click events and/or third labels associated with the accidental click events and/or the skip events. The second labels may correspond to an intentional click classification. The third labels may be based upon the accidental click probabilities. Click probabilities associated with content items may be determined using the first machine learning model. A content item may be selected for presentation via a client device based upon the click probabilities.
    Type: Grant
    Filed: June 14, 2021
    Date of Patent: January 24, 2023
    Assignee: YAHOO AD TECH LLC
    Inventors: Naama Haramaty-Krasne, Yohay Kaplan, Oren Shlomo Somekh, Alexander Shtoff
  • Publication number: 20220398180
    Abstract: In an example, sets of event information associated with events may be identified. The events may include intentional click events, accidental click events and/or skip events. Accidental click probabilities associated with the accidental click events and/or the skip events may be determined. Machine learning model training may be performed, using the sets of event information associated with the events and labels associated with the events, to generate a first machine learning model. The labels may include second labels associated with the intentional click events and/or third labels associated with the accidental click events and/or the skip events. The second labels may correspond to an intentional click classification. The third labels may be based upon the accidental click probabilities. Click probabilities associated with content items may be determined using the first machine learning model. A content item may be selected for presentation via a client device based upon the click probabilities.
    Type: Application
    Filed: June 14, 2021
    Publication date: December 15, 2022
    Inventors: Naama Haramaty-Krasne, Yohay Kaplan, Oren Shlomo Somekh, Alexander Shtoff