公开(公告)号：US20190005409A1

公开(公告)日：2019-01-03

申请号：US15639885

申请日：2017-06-30

Applicant: Facebook, Inc.

Inventor： Harsh Doshi ,  Kai Ren ,  Sagar Chordia

IPC: G06N99/00 ,  G06N5/04

Abstract: Methods and systems are described herein for jointly training embeddings. The method involves identifying a first data set describing occurrences of a first event type and identifying a second data set describing occurrences of a second event type, in which the first data set and the second data set include a set of users in common. The method further involves jointly training a set of embeddings a joint set of users, involving training the set of users in common based on co-occurrences of events of the first event type first data set and co-occurrences of events of the second event type in the second data set. The method further involves training a computer model that predicts the likelihood of occurrence of a future event for a user with respect to a content item based on the embedding for the user in the jointly trained set of embeddings.

公开(公告)号：US20180293611A1

公开(公告)日：2018-10-11

申请号：US15482447

申请日：2017-04-07

Applicant: Facebook, Inc.

Inventor： Sagar Chordia ,  Kai Ren ,  Adiitya Pal ,  Amac Herdagdelen ,  Tian Wang

IPC: G06Q30/02 ,  H04L29/08 ,  G06N99/00 ,  G06N5/04

Abstract: A primary online system infers interests for its users based on interest information in a secondary online system. Users that have user profiles in both the primary online system and the secondary online system are identified, and those associated with a target interest in the secondary online system are selected as part of a training group of that is used to generate an interest inference model that associates information in the training group's user profiles in the primary online system with the target interest. The interest inference model is applied to an input group of users in the primary online system to identify a seed group of users for whom the target interest can be inferred. The primary online system can then target content related to the target interest to an expanded group of users generated based on the seed group.