公开(公告)号：US11507974B2

公开(公告)日：2022-11-22

申请号：US17384220

申请日：2021-07-23

Applicant: Meta Platforms, Inc.

Inventor： Anand Sumatilal Bhalgat ,  Chinmay Deepak Karande

IPC: G06Q30/02 ,  G06Q50/00

Abstract: A social networking system provides content items to a user via a feed that may include one or more sponsored content items. Multiple sponsored content items may be included in a set that is presented in the feed via a scrollable content unit that presents a sponsored content item from the set and presents additional sponsored content items from the set when user interaction is received. To place sponsored content items in the feed, the social networking system scores a set of sponsored content items based on prior user interactions with content presented via scrollable content units and a bid amount of a sponsored content item in the set. The set of sponsored content items is ranked among other sponsored content items based on its score. If the set of sponsored content items is selected for inclusion in the feed, the social networking system orders the sponsored content items in the set for presentation via the scrollable content unit.

公开(公告)号：US20240028933A1

公开(公告)日：2024-01-25

申请号：US17118460

申请日：2020-12-10

Applicant: Meta Platforms, Inc.

Inventor： Christian Alexander Martine ,  Robert Oliver Burns Zeldin ,  Dinkar Jain ,  Jurgen Anne Francois Marie Van Gael ,  Anand Sumatilal Bhalgat ,  Tianshi Gao

IPC: G06N7/00 ,  H04L29/08 ,  G06N20/00

CPC classification number: G06N7/005 ,  H04L67/22 ,  G06N20/00 ,  H04L67/20 ,  G06Q30/0202

Abstract: A system predicts user intent to take an action and delivers content items to the user that match that intent. A plurality of features or attributes for each tracking pixel in a set of tracking pixels can be acquired based on content items and landing pages associated with each tracking pixel. For example, features for a tracking pixel can be determined based on information associated with a content item that enabled a user to access a landing page from which the tracking pixel was fired or triggered. In this example, features for the tracking pixel can also be determined based on information associated with the landing page. The features for the tracking pixels can be utilized to train a machine learning model. The machine learning model can be trained to predict whether or not a particular user intends to produce a conversion (e.g., make a purchase).