Facebook, Inc.

Sanjeet Uday Hajarnis

Varun Kacholia

David Vickrey

Guy Dassa

Holly Marie Ormseth

Sahil Prakash Thaker

Khalid Bakry El-Arini

Yuanxuan Wang

Elad Gerson

Prasoon Mishra

Amey Ajit Porobo Dharwadker

Gaurav Shankar

An embedding vector is the determined for a target user based on a weighted sum or the embedding vectors of entities the target user has interacted with in the past. Then, for each entity of a plurality of entities of the online system, a measure of similarity between the embedding vector of the user and the embedding vectors of the plurality of entities is determined. Based on the measure of similarity of each of the entities, the plurality of entities are ranked and one or more entities are selected to be presented to the user.

Embeddings for feed and pages

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.

Systems and methods for recommending follow up content

Growing community of inventors

Sunnyvale, CA, United States of America

Sanjeet Uday Hajarnis