公开(公告)号：US20230028389A1

公开(公告)日：2023-01-26

申请号：US17382031

申请日：2021-07-21

Applicant: Verizon Patent and Licensing Inc.

Inventor： Vamshi Gillipalli ,  Haripriya Srinivasaraghavan ,  Yogalakshmi Narayanasamy ,  Praveen Kumar Bandaru ,  Sirisha Sripathi ,  Abhishek A. Desai ,  Zhiqun Wang

IPC: H04N21/25 ,  H04N21/482 ,  H04N21/454 ,  G06F16/735 ,  G06F16/738

Abstract: Disclosed is a system for generating personalized recommendations based on dynamic and customized content selections and modeling of the content selections. The system may receive a request with an identifier and a query, and may obtain a particular recommendation configuration based the identifier and the query. The system may retrieve a set of content that satisfies the query and that is identified with at least one content prioritization parameter specified in the particular recommendation configuration, may generate a set of models of one or more model types that model relevance between the set of content and a different event specified in the particular recommendation configuration, and may compute a score for each content in each model based on the modeled relevance. The system may present recommended content in a different order than the set of content based on aggregate scores compiled for each content from the set of models.

公开(公告)号：US11689755B2

公开(公告)日：2023-06-27

申请号：US17382031

申请日：2021-07-21

Applicant: Verizon Patent and Licensing Inc.

Inventor： Vamshi Gillipalli ,  Haripriya Srinivasaraghavan ,  Yogalakshmi Narayanasamy ,  Praveen Kumar Bandaru ,  Sirisha Sripathi ,  Abhishek A. Desai ,  Zhiqun Wang

IPC: H04N21/25 ,  H04N21/482 ,  G06F16/738 ,  G06F16/735 ,  H04N21/454

CPC classification number: H04N21/251 ,  G06F16/735 ,  G06F16/738 ,  H04N21/454 ,  H04N21/4826

Abstract: Disclosed is a system for generating personalized recommendations based on dynamic and customized content selections and modeling of the content selections. The system may receive a request with an identifier and a query, and may obtain a particular recommendation configuration based the identifier and the query. The system may retrieve a set of content that satisfies the query and that is identified with at least one content prioritization parameter specified in the particular recommendation configuration, may generate a set of models of one or more model types that model relevance between the set of content and a different event specified in the particular recommendation configuration, and may compute a score for each content in each model based on the modeled relevance. The system may present recommended content in a different order than the set of content based on aggregate scores compiled for each content from the set of models.