Invention Grant
- Patent Title: Advertisement conversion prediction based on unlabeled data
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Application No.: US15091105Application Date: 2016-04-05
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Publication No.: US10592921B2Publication Date: 2020-03-17
- Inventor: Sameer Indarapu , Pradheep K. Elango , Xian Xu
- Applicant: Facebook, Inc.
- Applicant Address: US CA Menlo Park
- Assignee: Facebook, Inc.
- Current Assignee: Facebook, Inc.
- Current Assignee Address: US CA Menlo Park
- Agency: FisherBroyles, LLP
- Main IPC: G06Q30/00
- IPC: G06Q30/00 ; G06Q30/02 ; G06N20/00

Abstract:
Embodiments are disclosed for predicting target events occurrence for an advertisement campaign. A computing device according to some embodiments assigns a label to an advertisement as unlabeled, in response to a notification that a prerequisite event occurs for the advertisement. The device generates feature vectors based on data that relate to the advertisement. The device further trains a machine learning model using the feature vectors of the unlabeled advertisement based on a first term of an objective function, without waiting for a target event for the advertisement to occur. The first term depends on unlabeled advertisements. The device predicts a probability of a target event occurring for a new advertisement, by feeding data of the new advertisement to the trained machine learning model.
Public/Granted literature
- US20170286997A1 ADVERTISEMENT CONVERSION PREDICTION BASED ON UNLABELED DATA Public/Granted day:2017-10-05
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