Abstract: Described herein is a technique to facilitate filtering during candidate retrieval stage performed by an information retrieval system that utilizes embedding models. An aNN indexing structure is created for each end-user, and in some instances, each activity type. This allows a single request for candidate content items to invoke a single process to obtain content items that satisfy the filtering criteria (e.g., in this case, the in-network requirement) from the separate per-end-user indexes.

Abstract: Described herein is a technique to facilitate filtering during candidate retrieval stage performed by an information retrieval system that utilizes embedding models. An aNN indexing structure is created for each end-user, and in some instances, each activity type. This allows a single request for candidate content items to invoke a single process to obtain content items that satisfy the filtering criteria (e.g., in this case, the in-network requirement) from the separate per-end-user indexes.

Abstract: Described herein is a technique for surfacing content for users of a connection network application. The technique involves performing a first query to fetch recently-impressed items viewed by a user of the connection network application and, concurrently with the first query, performing a second query of search nodes to generate a set of search node results. The technique allows for filtering the recently-impressed items from the set of search node results to generate a candidate set and applying a freshness factor to the candidate set. Updates are provided to a user display, based on results of applying the freshness factor to the candidate set.