Abstract: An on-line social network system is configured to generate a news feed for a member by processing updates originating from different sources using different first pass ranker models. The first pass ranker models generate respective sets of raw scores, which are calibrated based on a consistent scale of feed engagement metrics of interest, such as a click through rate. The calibrated scores are then used as training data to train a second pass ranker and/or as input into the second pass ranker at the time when the second pass ranker is to generate respective ranks for items in an inventory of updates identified as potentially of interest to a focus member and to select a subset of items from the inventory based on the generated respective ranks.

Abstract: A machine may be configured to generate a digital content feed based on at least explicit feedback from a member of a Social Networking Service (SNS). For example, the machine generates explicit input data describing digital content preferences of a member of the SNS based on a communication including explicit feedback data. The communication is received from a client device associated with the member. The machine accesses feature data pertaining to one or more items of digital content determined to be relevant to the member. The feature data describes one or more characteristics associated with the one or more items. The machine generates a feed of items of digital content for the member based on the explicit input data and the feature data. The machine causes a presentation of the feed of the items of digital content in a user interface of the client device associated with the user.

Abstract: A news feed system of an on-line social network system obtains and utilizes data related to events that originate with members of the on-line social network system from web pages other those members' news feed pages. The news feed system monitors signals that are not related to feed interaction and generates contextual engagement features based on those signals. The news feed system associates contextual engagement features with respective member profiles and may store the association information for a period of time. The news feed system then uses these features to train a model that ranks news feed inventory and/or as input into that model.

Abstract: A news feed system of an on-line social network system news utilizes a relevance model to determine which updates from an inventory of updates are to be presented to a member on their news feed page. The relevance model is trained using historical data that reflects interactions of members of the on-line social network system with items in their respective news feed pages. In order to reduce potential biases in the historical data that is used to train the relevance model, the news feed system designates a certain portion of all member sessions to be random sessions. The news feed generated for a member during a random session includes updates that are selected and/or ordered for presentation using one or more randomization techniques.

Abstract: A machine may be configured to generate a digital content feed based on at least explicit feedback from a member of a Social Networking Service (SNS). For example, the machine generates explicit input data describing digital content preferences of a member of the SNS based on a communication including explicit feedback data. The communication is received from a client device associated with the member. The machine accesses feature data pertaining to one or more items of digital content determined to be relevant to the member. The feature data describes one or more characteristics associated with the one or more items. The machine generates a feed of items of digital content for the member based on the explicit input data and the feature data. The machine causes a presentation of the feed of the items of digital content in a user interface of the client device associated with the user.

Abstract: A news feed system of an on-line social network system obtains and utilizes data related to events that originate with members of the on-line social network system from web pages other those members' news feed pages. The news feed system monitors signals that are not related to feed interaction and generates contextual engagement features based on those signals. The news feed system associates contextual engagement features with respective member profiles and may store the association information for a period of time. The news feed system then uses these features to train a model that ranks news feed inventory and/or as input into that model.

Abstract: An on-line social network system is configured to generate a news feed for a member by processing updates originating from different sources using different first pass ranker models. The first pass ranker models generate respective sets of raw scores, which are calibrated based on a consistent scale of feed engagement metrics of interest, such as a click through rate. The calibrated scores are then used as training data to train a second pass ranker and/or as input into the second pass ranker at the time when the second pass ranker is to generate respective ranks for items in an inventory of updates identified as potentially of interest to a focus member and to select a subset of items from the inventory based on the generated respective ranks.

Abstract: An on-line social network system includes a ranker to processes an inventory of news feed updates for a member and select more relevant updates for presentation to the member. The ranker is trained using training data that includes personalized engagement probability for an update. The personalized engagement probability values are calculated in real time and for a particular update with respect to member features that appear in member profiles maintained by the on-line social network system.

Abstract: A news feed system is provided to generate augmented news feed for a member of an on-line social network. When a request is detected to construct a news feed for a member in an on-line social network system, the news feed system determines a cohort of the member and, from the updates that are being presented in their respective news feeds to members of the cohort, selects a leaderboard set of updates. The leaderboard set of updates is used in constructing a news feed web page for the member.