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公开(公告)号:US11443347B2
公开(公告)日:2022-09-13
申请号:US17006495
申请日:2020-08-28
Applicant: Samsung Electronics Co., Ltd.
Inventor: Xianshan Qu , Li Li , Xi Liu , Rui Chen , Yong Ge , Soo-Hyun Choi
Abstract: A system and method capable of learning dynamic user and advertisement behavior for more effective click-through rate prediction. The system and method include at least one processor configured to obtain at least one item data, wherein the at least one item data comprises at least one explicit feedback to a user interaction event and other data associated with an item. The at least one processor also uses an interaction model that incorporates the obtained at least one item data to generate a user response prediction for a user and another interaction event.
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公开(公告)号:US20210365818A1
公开(公告)日:2021-11-25
申请号:US17318808
申请日:2021-05-12
Applicant: Samsung Electronics Co., Ltd.
Inventor: Ninghao Liu , Yong Ge , Li Li , Xia Hu , Rui Chen , Soo-Hyun Choi
Abstract: A method includes obtaining, by an electronic device, an interpretation hierarchy generated based on a knowledge graph and behavioral data. The method also includes performing, by the electronic device, graph convolution operations on the interpretation hierarchy to generate one or more embeddings. The method further includes generating, by the electronic device, a recommendation based at least in part on associations between the one or more embeddings. In addition, the method includes providing, by the electronic device, an explanation corresponding to the recommendation.
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公开(公告)号:US20210065251A1
公开(公告)日:2021-03-04
申请号:US17006495
申请日:2020-08-28
Applicant: Samsung Electronics Co., Ltd.
Inventor: Xianshan Qu , Li Li , Xi Liu , Rui Chen , Yong Ge , Soo-Hyun Choi
Abstract: A system and method capable of learning dynamic user and advertisement behavior for more effective click-through rate prediction. The system and method include at least one processor configured to obtain at least one item data, wherein the at least one item data comprises at least one explicit feedback to a user interaction event and other data associated with an item. The at least one processor also uses an interaction model that incorporates the obtained at least one item data to generate a user response prediction for a user and another interaction event
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