Patents by Inventor David Vickrey

David Vickrey 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: 10740690
    Abstract: An online system predicts topics for content items. The online system provides one or more topic labels for a user to apply concurrently while a user is composing a post, in response to requests periodically received from the user's device. A request includes information such as content composed by the user and contextual information. The online system employs machine learning techniques to analyze content composed by a user and contextual information thereby to predict topic labels. Different machine learning models for classifying individual topic labels, identifying relevant topic labels, and/or detecting changes in existing topic predictions are developed. Some machine learning models predict topics for full content and some predict topics for partial content. The online system trains the machine learning models to ensure accurate topic predictions are provided timely. The online system employs various machine learning model training methods such as active training and gradient training.
    Type: Grant
    Filed: March 24, 2017
    Date of Patent: August 11, 2020
    Assignee: Facebook, Inc.
    Inventors: Jeffrey William Pasternack, David Vickrey, Justin MacLean Coughlin, Prasoon Mishra, Austen Norment McDonald, Max Christian Eulenstein, Jianfu Chen, Kritarth Anand, Polina Kuznetsova
  • Patent number: 10733254
    Abstract: An online system, such as a social networking system, monitors user interactions with news feed stories of the social networking system and divides the user interactions into non-content clicks and content clicks. The non-content clicks indicate a user's interest in news feed stories based on user actions such as comments on, likes, shares, and hides the news feed stories. The content clicks indicate a user's interest in news feed stories based on user actions on different specific portions of multimedia content (e.g., videos) in the news feed stories such as playing, fast forwarding. The social networking system trains a model based on the monitored user interactions with news feed stories and uses the trained model to rank news feed stories for presentation to a user. The ranks of news feed stories for a user are determined based on a likelihood that the user would find the story interesting.
    Type: Grant
    Filed: December 10, 2015
    Date of Patent: August 4, 2020
    Assignee: Facebook, Inc.
    Inventors: Gregory Matthew Marra, David Vickrey, Mahmud Sami Tas, Yue Zhuo
  • Patent number: 10558714
    Abstract: An online system ranks topic-groups for users and presents content items in topic-based feeds. A topic group corresponds to one or more topic(s) and can be used to generate a feed for presenting the content items related to the topic(s). For a particular user, the topic groups are ranked according to the likelihood of the user interacting with content items included in the topic groups. The topic groups are ranked using information of the users and/or users' historical interaction data such as click-based interaction data, post-based interaction data, or engagement-based interaction data. The online system generates and provides a user interface for presenting the topic groups to the client device. Content items that are related to the topic(s) corresponding to the topic group are presented in each topic-based feed such that the user can switch between different topic-based feeds.
    Type: Grant
    Filed: December 28, 2016
    Date of Patent: February 11, 2020
    Assignee: Facebook, Inc.
    Inventors: Shengbo Guo, Annie Hsin-Wen Liu, David Vickrey, Khalid Bakry El-Arini
  • Patent number: 10484489
    Abstract: An online system generates a feed of content for a user that includes content items provided by, or otherwise related to, other users who are connected to the user via the online system. The online system supplements the feed with additional content items that are not related to users who are connected to the user but are likely to be of interest to the user. The additional content items may be associated with users who are connected to additional users who are connected to the user, content items having received a threshold amount of interacting by other users, content items provided by users who provided other content with which the user interacted, or have other characteristics. The additional content items and content items associated with users connected to the user are included in one or more selection processes that generate the feed for the user.
    Type: Grant
    Filed: December 29, 2016
    Date of Patent: November 19, 2019
    Assignee: Facebook, Inc.
    Inventors: Khalid Bakry El-Arini, David Vickrey
  • Patent number: 10353963
    Abstract: A social networking system receives messages from users that include links to webpages that designate keywords of the webpage. The social networking system identifies webpages linked by users to generate computer models that predict whether a webpage or message should be associated with particular keywords. The social networking system generates computer models that are trained on example webpages and related keywords linked by users in messages. Prior to generating computer models, the social networking system applies one or more filters to exclude webpages and keywords from consideration. The filters may exclude webpages that have low-reliability, are associated with an excessive number of keywords, or keywords that appear on an insufficient number of domains. After training the computer models, messages composed by users may be analyzed and a keyword predicted for the message, which may be suggested to the user to categorize the message.
    Type: Grant
    Filed: December 19, 2014
    Date of Patent: July 16, 2019
    Assignee: Facebook, Inc.
    Inventors: David Vickrey, Jeffrey William Pasternack
  • Patent number: 10318597
    Abstract: Systems, methods, and non-transitory computer readable media configured to detect access by a user to an original content item relating to a story. At least one of a comments based technique, a token based technique, and a tag based technique is performed on content items. Constraints are applied to identify at least one follow up content item from the content items relating to a development of the story.
    Type: Grant
    Filed: December 22, 2014
    Date of Patent: June 11, 2019
    Assignee: Facebook, Inc.
    Inventors: Holly Marie Ormseth, Elad Gerson, Guy Dassa, Khalid Bakry El-Arini, Gaurav Shankar, Yuanxuan Wang, Varun Kacholia, Prasoon Mishra, David Vickrey, Sanjeet Uday Hajarnis, Sahil P. Thaker
  • Patent number: 10311525
    Abstract: A social networking system classifies content items according to their qualities for ranking and selection of content items to present to users within, for example, a newsfeed. Low-quality content items that are unlikely to be interesting or relevant to a user may be distinguished though they may appear to be popular among users in the social networking system. The social networking system identifies within the content items one or more features that are indicators of the quality of the content items. The social networking system can use one or more classifiers to evaluate the content items based on the features, and it can compute a quality metric indicating the quality of a content item based on the result obtained from the classifiers. The quality metric can be used in the ranking and selection of a set of content items to provide to the user.
    Type: Grant
    Filed: March 5, 2018
    Date of Patent: June 4, 2019
    Assignee: Facebook, Inc.
    Inventors: Erich James Owens, David Vickrey
  • Patent number: 10282384
    Abstract: Systems, methods, and non-transitory computer readable media configured to determine a value of a utility factor associated with a content item corresponding to a link. An optimized utility value relating to an interaction type of an outbound click is determined based on the value of the utility factor. An expected utility score associated with the content item is generated based on the optimized utility value to determine potential presentation of the content item to a user.
    Type: Grant
    Filed: December 29, 2014
    Date of Patent: May 7, 2019
    Assignee: Facebook, Inc.
    Inventors: Joyce Tang, Khalid Bakry El-Arini, David Vickrey
  • Publication number: 20190109871
    Abstract: The present disclosure relates to techniques for determining trustworthiness of a domain among users. The determination may be based upon trust scores provided by the users for the domain. When all users have specified a trust score for the domain, an overall trust score may be computed based upon the specified trust scores. When some users have not specified a trust score for the domain, trust scores may be computed for the users based upon the specified trust scores, and an overall trust score may be computed based upon the specified trust scores and the computed trust scores. Based on the overall trust score, a social networking system may send content to users of the social networking system.
    Type: Application
    Filed: October 10, 2017
    Publication date: April 11, 2019
    Inventors: David Vickrey, Alexander Calan Leavitt, Anavil Tripathi, Harsh Mayur Selani, Prasoon Mishra, Sara Lee Su, Grace Louise Jackson
  • Patent number: 10122808
    Abstract: An online system receives a posted content item from a posting user. The online system labels the posted content item with an audience, the audience being a subset of a group of users having an affinity to a topic of the online system, the subset of the group of users sharing a particular treatment regarding the topic. After identifying an opportunity to present content to a viewing user, the online system selects candidate content items, and scores each candidate content item by determining whether the candidate content item is associated with an audience that includes the viewing user, and if so, modifying the score of the candidate content item to be higher. The online system ranks the candidate content items based on the associated score, selects a subset of the candidate content items based on the associated ranking, and presents the selected subset to the viewing user.
    Type: Grant
    Filed: April 8, 2016
    Date of Patent: November 6, 2018
    Assignee: Facebook, Inc.
    Inventors: David Vickrey, Khalid Bakry El-Arini
  • Publication number: 20180276561
    Abstract: An online system predicts topics for content items. The online system provides one or more topic labels for a user to apply concurrently while a user is composing a post, in response to requests periodically received from the user's device. A request includes information such as content composed by the user and contextual information. The online system employs machine learning techniques to analyze content composed by a user and contextual information thereby to predict topic labels. Different machine learning models for classifying individual topic labels, identifying relevant topic labels, and/or detecting changes in existing topic predictions are developed. Some machine learning models predict topics for full content and some predict topics for partial content. The online system trains the machine learning models to ensure accurate topic predictions are provided timely. The online system employs various machine learning model training methods such as active training and gradient training.
    Type: Application
    Filed: March 24, 2017
    Publication date: September 27, 2018
    Inventors: Jeffrey William Pasternack, David Vickrey, Justin MacLean Coughlin, Prasoon Mishra, Austen Norment McDonald, Max Christian Eulenstein, Jianfu Chen, Kritarth Anand, Polina Kuznetsova
  • Patent number: 10063513
    Abstract: A social networking system generates stories based on actions of users in the system and provides a newsfeed to users that contain stories that related to one or more of their friends in the system. Although the story ranking algorithm includes a time decay to penalize older stories, stories may actually become stale at different rates. To measure the staleness of a story, the system computes a ratio of a current engagement rate for the story to an average engagement rate for the story. Based on this ratio, the system may filter out stale stories, includes the ratio as a feature in the scoring model, and/or adjust the decay rate.
    Type: Grant
    Filed: November 6, 2014
    Date of Patent: August 28, 2018
    Assignee: Facebook, Inc.
    Inventors: Erich James Owens, David Vickrey
  • Publication number: 20180191847
    Abstract: An online system generates a feed of content for a user that includes content items provided by, or otherwise related to, other users who are connected to the user via the online system. The online system supplements the feed with additional content items that are not related to users who are connected to the user but are likely to be of interest to the user. The additional content items may be associated with users who are connected to additional users who are connected to the user, content items having received a threshold amount of interacting by other users, content items provided by users who provided other content with which the user interacted, or have other characteristics. The additional content items and content items associated with users connected to the user are included in one or more selection processes that generate the feed for the user.
    Type: Application
    Filed: December 29, 2016
    Publication date: July 5, 2018
    Inventors: Khalid Bakry El-Arini, David Vickrey
  • Publication number: 20180181572
    Abstract: An online system ranks topic-groups for users and presents content items in topic-based feeds. A topic group corresponds to one or more topic(s) and can be used to generate a feed for presenting the content items related to the topic(s). For a particular user, the topic groups are ranked according to the likelihood of the user interacting with content items included in the topic groups. The topic groups are ranked using information of the users and/or users' historical interaction data such as click-based interaction data, post-based interaction data, or engagement-based interaction data. The online system generates and provides a user interface for presenting the topic groups to the client device. Content items that are related to the topic(s) corresponding to the topic group are presented in each topic-based feed such that the user can switch between different topic-based feeds.
    Type: Application
    Filed: December 28, 2016
    Publication date: June 28, 2018
    Inventors: Shengbo Guo, Annie Hsin-Wen Liu, David Vickrey, Khalid Bakry El-Arini
  • Patent number: 9959503
    Abstract: A social networking system receives messages from users that include hashtags. The social networking system may use a natural language model to identify terms in the hashtag corresponding to words or phrases of the hashtag. The words or phrases may be used to modify a string of the hashtag. The social networking system may also generate computer models to determine likely membership of a message with various hashtags. Prior to generating the computer models, the social networking system may filter certain hashtags from eligibility for computer modeling, particularly hashtags that are not frequently used or that more typically appear as normal text in a message instead of as a hashtag. The social networking system may also calibrate the computer model outputs by comparing a test message output with outputs of a calibration group that includes positive and negative examples with respect to the computer model output.
    Type: Grant
    Filed: December 31, 2014
    Date of Patent: May 1, 2018
    Assignee: Facebook, Inc.
    Inventors: David Vickrey, Jeffrey William Pasternack
  • Patent number: 9928556
    Abstract: A social networking system classifies content items according to their qualities for ranking and selection of content items to present to users within, for example, a newsfeed. Low-quality content items that are unlikely to be interesting or relevant to a user may be distinguished though they may appear to be popular among users in the social networking system. The social networking system identifies within the content items one or more features that are indicators of the quality of the content items. The social networking system can use one or more classifiers to evaluate the content items based on the features, and it can compute a quality metric indicating the quality of a content item based on the result obtained from the classifiers. The quality metric can be used in the ranking and selection of a set of content items to provide to the user.
    Type: Grant
    Filed: December 31, 2014
    Date of Patent: March 27, 2018
    Assignee: Facebook, Inc.
    Inventors: Erich James Owens, David Vickrey
  • Publication number: 20170295249
    Abstract: An online system receives a posted content item from a posting user. The online system labels the posted content item with an audience, the audience being a subset of a group of users having an affinity to a topic of the online system, the subset of the group of users sharing a particular treatment regarding the topic. After identifying an opportunity to present content to a viewing user, the online system selects candidate content items, and scores each candidate content item by determining whether the candidate content item is associated with an audience that includes the viewing user, and if so, modifying the score of the candidate content item to be higher. The online system ranks the candidate content items based on the associated score, selects a subset of the candidate content items based on the associated ranking, and presents the selected subset to the viewing user.
    Type: Application
    Filed: April 8, 2016
    Publication date: October 12, 2017
    Inventors: David Vickrey, Khalid Bakry El-Arini
  • Publication number: 20170171139
    Abstract: An online system, such as a social networking system, monitors user interactions with news feed stories of the social networking system and divides the user interactions into non-content clicks and content clicks. The non-content clicks indicate a user's interest in news feed stories based on user actions such as comments on, likes, shares, and hides the news feed stories. The content clicks indicate a user's interest in news feed stories based on user actions on different specific portions of multimedia content (e.g., videos) in the news feed stories such as playing, fast forwarding. The social networking system trains a model based on the monitored user interactions with news feed stories and uses the trained model to rank news feed stories for presentation to a user. The ranks of news feed stories for a user are determined based on a likelihood that the user would find the story interesting.
    Type: Application
    Filed: December 10, 2015
    Publication date: June 15, 2017
    Inventors: Gregory Matthew Marra, David Vickrey, Mahmud Sami Tas, Yue Zhuo
  • Patent number: 9582786
    Abstract: Machine learning models are used for ranking news feed stories presented to users of a social networking system. The social networking system divides its users into different sets, for example, based on demographic characteristics of the users and generates one model for each set of users. The models are periodically retrained. The news feed ranking model may rank news feeds for a user based on information describing other users connected to the user in the social networking system. Information describing other users connected to the user includes interactions of the other users with objects associated with news feed stories. These interactions include commenting on a news feed story, liking a news feed story, or retrieving information, for example, images, videos associated with a news feed story.
    Type: Grant
    Filed: July 29, 2011
    Date of Patent: February 28, 2017
    Assignee: Facebook, Inc.
    Inventors: Max Gubin, Wayne Kao, David Vickrey, Alexey Maykov
  • Patent number: 9569727
    Abstract: A social networking system receives messages from users that include hashtags. The social networking system may use a natural language model to identify terms in the hashtag corresponding to words or phrases of the hashtag. The words or phrases may be used to modify a string of the hashtag. The social networking system may also generate computer models to determine likely membership of a message with various hashtags. Prior to generating the computer models, the social networking system may filter certain hashtags from eligibility for computer modeling, particularly hashtags that are not frequently used or that more typically appear as normal text in a message instead of as a hashtag. The social networking system may also calibrate the computer model outputs by comparing a test message output with outputs of a calibration group that includes positive and negative examples with respect to the computer model output.
    Type: Grant
    Filed: December 31, 2014
    Date of Patent: February 14, 2017
    Assignee: Facebook, Inc.
    Inventors: David Vickrey, Jeffrey William Pasternack