公开(公告)号：US20230077829A1

公开(公告)日：2023-03-16

申请号：US17474188

申请日：2021-09-14

Applicant: Adobe Inc.

Inventor： Sana Malik Lee ,  Zhuohao Zhang ,  Zhicheng Liu ,  Tak Yeon Lee ,  Shunan Guo ,  Ryan A. Rossi ,  Fan Du ,  Eunyee Koh

IPC: G06Q10/06 ,  G06N20/00 ,  G06T11/20 ,  G06T11/60

Abstract: In implementations of systems for generating interactive reports, a computing device implements a report system to receive input data describing a dataset and an analytics report for the dataset that depicts a result of performing analytics on the dataset. The report system generates a declarative specification that describes the analytics report in a language that encodes data as properties of graphic objects. Editing data is received describing a user input specifying a modification to the analytics report. The report system modifies the declarative specification using the language that encodes data as properties of graphic objects based on the user input and the dataset. An interactive report is generated based on the modified declarative specification that includes the analytics report having the modification.

公开(公告)号：US20230030341A1

公开(公告)日：2023-02-02

申请号：US17383114

申请日：2021-07-22

Applicant: Adobe Inc.

Inventor： Eunyee Koh ,  Tak Yeon Lee ,  Andrew Thomson ,  Vasanthi Holtcamp ,  Ryan Rossi ,  Fan Du ,  Caroline Kim ,  Tong Yu ,  Shunan Guo ,  Nedim Lipka ,  Shriram Venkatesh Shet Revankar ,  Nikhil Belsare

IPC: G06N3/08 ,  H04L12/26 ,  G06F40/186 ,  G06N3/04

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a dynamic user interface and machine learning tools to generate data-driven digital content and multivariate testing recommendations for distributing digital content across computer networks. In particular, in one or more embodiments, the disclosed systems utilize machine learning models to generate digital recommendations at multiple development stages of digital communications that are targeted on particular performance metrics. For example, the disclosed systems utilize historical information and recipient profile data to generate recommendations for digital communication templates, fragment variants of content fragments, and content variants of digital content items. Ultimately, the disclosed systems generate multivariate testing recommendations incorporating selected fragment variants to intelligently narrow multivariate testing candidates and generate more meaningful and statistically significant multivariate testing results.