-
公开(公告)号：US20190172089A1
公开(公告)日：2019-06-06
申请号：US15829841
申请日：2017-12-01
Applicant: Facebook, Inc.
Inventor： Junbiao Tang , Alexander Pivovarov , Anand Sumatilal Bhalgat , Janis Libeks , Hao Zhang , Yevgeniya Solyanik
IPC: G06Q30/02
Abstract: An online system determines an estimated conversion rate for sponsored content items placed on content publishers and on the online system. The estimated conversion rate can be determined by a machine learning model trained using data describing content campaigns, content publishers, and online system users. This data is collected by the online system from content publishers and/or content campaigns that report conversion rates to the online system. By determining a ratio of estimated conversion rates with third party content on the content publisher against those on the online system, the online system can determine a publisher quality score for that content publisher. The online system uses the publisher quality score to normalize third party value contributions toward placing sponsored content on content publishers and the online system. Thus, disparities in the intrinsic value across publishers are diminished as third party value contributions are normalized based on the publisher conversion rates.
-
Patent Agency Ranking
2.发明申请公开(公告)号：US20180121953A1
公开(公告)日：2018-05-03
申请号：US15340855
申请日：2016-11-01
Applicant: Facebook, Inc.
Inventor： Zhurun Zhang , Junbiao Tang , Anwar Saipulla , Zhonghua Qu , Yevgeniya Solyanik , Avi Samuel Gavlovski
CPC classification number: G06Q30/0254 , G06N5/003 , G06N20/00 , G06Q30/0276
Abstract: An online system receives multiple candidate components for including in content items to be presented to online system users. Upon identifying an opportunity to present content to a subject user of the online system, the online system dynamically generates an optimal content item for presentation to the subject user that includes one or more candidate components. Candidate components included in the optimal content item are associated with a predicted marginal effect on a performance metric associated the optimal content item. This marginal effect may be predicted using a machine-learned model that is trained using historical performance information about content items that were presented to viewing users of the online system having at least a threshold measure of similarity to the subject user and one or more features associated with candidate components included in these content items and in the optimal content item.
-
公开(公告)号：US20170308512A1
公开(公告)日：2017-10-26
申请号：US15136559
申请日：2016-04-22
Applicant: Facebook, Inc.
Inventor： Junbiao Tang , Ewa Dominowska , Hua Chen , Jennifer Anne Abrahamson , Abhishek Agarwal
CPC classification number: G06F17/2247 , G06F17/30702 , G06F17/30867 , G06Q10/00 , H04L67/02 , H04L67/20 , H04L67/306
Abstract: An online system maintains information identify a context in which sponsored content items were presented to users. A context in which a sponsored content item was presented to a user identifies additional content presented to the user prior to the sponsored content item, and may identify additional content presented in conjunction with the sponsored content item. The online system identifies users to whom at least one sponsored content item was presented in a context and generates characteristics for the context based on characteristics of users who were presented with at least one sponsored content item in the context. When the online system receives a request to present sponsored content items in the context that does not identify an online system user, the online system selects sponsored content items for the request based on the generated characteristics for the context.
-
公开(公告)号：US11232482B2
公开(公告)日：2022-01-25
申请号：US15340855
申请日：2016-11-01
Applicant: Facebook, Inc.
Inventor： Zhurun Zhang , Junbiao Tang , Anwar Saipulla , Zhonghua Qu , Yevgeniya Solyanik , Avi Samuel Gavlovski
Abstract: An online system receives multiple candidate components for including in content items to be presented to online system users. Upon identifying an opportunity to present content to a subject user of the online system, the online system dynamically generates an optimal content item for presentation to the subject user that includes one or more candidate components. Candidate components included in the optimal content item are associated with a predicted marginal effect on a performance metric associated the optimal content item. This marginal effect may be predicted using a machine-learned model that is trained using historical performance information about content items that were presented to viewing users of the online system having at least a threshold measure of similarity to the subject user and one or more features associated with candidate components included in these content items and in the optimal content item.
-
5.发明申请公开(公告)号：US20180121964A1
公开(公告)日：2018-05-03
申请号：US15340852
申请日：2016-11-01
Applicant: Facebook, Inc.
Inventor： Zhurun Zhang , Hao Zhang , Junbiao Tang , James Theodore Kleban , Avi Samuel Gavlovski , Hao Song , David Benjamin Lue , Anand Sumatilal Bhalgat
CPC classification number: G06Q30/0269 , G06N20/00 , G06Q30/0277 , G06Q50/01
Abstract: An online system receives multiple candidate components for including in content items to be presented to online system users. Upon identifying an opportunity to present content to a subject user of the online system, the online system dynamically generates an optimal content item for presentation to the subject user that includes one or more candidate components. Candidate components included in the optimal content item are selected by predicting an affinity of the subject user for each candidate component. The affinity of the subject user for a candidate component may be predicted using a machine-learned model that is trained using historical performance information about content items including the candidate component that were presented to viewing users of the online system having at least a threshold measure of similarity to the subject user. Components of content items used to train the model may be selected using a heuristic (e.g., Thompson sampling).
-
公开(公告)号：US09959258B2
公开(公告)日：2018-05-01
申请号：US15136559
申请日：2016-04-22
Applicant: Facebook, Inc.
Inventor： Junbiao Tang , Ewa Dominowska , Hua Chen , Jennifer Anne Abrahamson , Abhishek Agarwal
CPC classification number: G06F17/2247 , G06F17/30702 , G06F17/30867 , G06Q10/00 , H04L67/02 , H04L67/20 , H04L67/306
Abstract: An online system maintains information identify a context in which sponsored content items were presented to users. A context in which a sponsored content item was presented to a user identifies additional content presented to the user prior to the sponsored content item, and may identify additional content presented in conjunction with the sponsored content item. The online system identifies users to whom at least one sponsored content item was presented in a context and generates characteristics for the context based on characteristics of users who were presented with at least one sponsored content item in the context. When the online system receives a request to present sponsored content items in the context that does not identify an online system user, the online system selects sponsored content items for the request based on the generated characteristics for the context.
-
-
-
-
-
Search Results
6
records
(took 0.013 seconds)
