公开(公告)号：US11170389B2

公开(公告)日：2021-11-09

申请号：US16796169

申请日：2020-02-20

Applicant: Adobe Inc.

Inventor： Haoliang Wang ,  Viswanathan Swaminathan ,  Stefano Petrangeli ,  Ran Xu

IPC: G06Q30/02 ,  G11B27/031

Abstract: Techniques are disclosed for improving media content effectiveness. A methodology implementing the techniques according to an embodiment includes generating an intermediate representation (IR) of provided media content, the IR specifying editable elements of the content and maintaining a result of cumulative edits to those elements. The method also includes editing the elements of the IR to generate a set of candidate IR variations. The method further includes creating a set of candidate media contents based on the candidate IR variations, evaluating the candidate media contents to generate effectiveness scores, and pruning the set of candidate IR variations to retain a threshold number of the candidate IR variations as surviving IR variations associated with the highest effectiveness scores. The process iterates until either an effectiveness score exceeds a threshold value, the incremental improvement at each iteration falls below a desired value, or a maximum number of iterations have been performed.

公开(公告)号：US20210264446A1

公开(公告)日：2021-08-26

申请号：US16796169

申请日：2020-02-20

Applicant: Adobe Inc.

Inventor： Haoliang Wang ,  Viswanathan Swaminathan ,  Stefano Petrangeli ,  Ran Xu

IPC: G06Q30/02 ,  G11B27/031

Abstract: Techniques are disclosed for improving media content effectiveness. A methodology implementing the techniques according to an embodiment includes generating an intermediate representation (IR) of provided media content, the IR specifying editable elements of the content and maintaining a result of cumulative edits to those elements. The method also includes editing the elements of the IR to generate a set of candidate IR variations. The method further includes creating a set of candidate media contents based on the candidate IR variations, evaluating the candidate media contents to generate effectiveness scores, and pruning the set of candidate IR variations to retain a threshold number of the candidate IR variations as surviving IR variations associated with the highest effectiveness scores. The process iterates until either an effectiveness score exceeds a threshold value, the incremental improvement at each iteration falls below a desired value, or a maximum number of iterations have been performed.