公开(公告)号：US20240144307A1

公开(公告)日：2024-05-02

申请号：US18047421

申请日：2022-10-18

Applicant: ADOBE INC.

Inventor： Tung Mai ,  Ritwik Sinha ,  Trevor Hyrum Paulsen ,  Xiang Chen ,  William Brandon George ,  Nate Purser ,  Zhao Song

IPC: G06Q30/02

CPC classification number: G06Q30/0204

Abstract: One aspect of systems and methods for segment size estimation includes identifying a segment of users for a first time period based on time series data, wherein the time series data includes a series of interactions between users and a content channel and wherein the segment includes a portion of the users interacting with the content channel during the first time period; computing a segment return value for a second time period based on the time series data by computing a first subset and a second subset of the segment, wherein the first subset includes users that interact with the content channel greater than a threshold number of times during a range of the time series data and the second subset comprises a complement of the first subset with respect to the segment; and providing customized content to a user in the segment based on the segment return value.

公开(公告)号：US20210326392A1

公开(公告)日：2021-10-21

申请号：US16853448

申请日：2020-04-20

Applicant: Adobe Inc.

Inventor： Ivan Ben Andrus ,  Trevor Hyrum Paulsen ,  Ritwik Sinha

IPC: G06F16/903 ,  G06F16/28 ,  G06F16/958

Abstract: Introduced is a technique for assigning attribution values associated with a metric to dimensions in a set of data. An attribution model can be implemented to process data to assign attribution values to the dimensions in the data. The attribution model can be configured accordingly to game theoretic properties such as Shapley value. For example, each of the dimensions in the data may correspond to a different player in a cooperative game based on a specified value function. Using the specified value function, attribution values associated with a metric can be assigned to the dimensions in the data. The introduced technique can be implemented to assign attribution value associated with various types of metric to various types of dimensions. Further, the introduced technique is highly scalable and can be implemented to process data at query time without requiring any offline models to be run.

公开(公告)号：US10289624B2

公开(公告)日：2019-05-14

申请号：US15065587

申请日：2016-03-09

Applicant: ADOBE INC.

Inventor： Trevor Hyrum Paulsen ,  Jaime Vasquez

IPC: G06F17/30 ,  G06F16/2457 ,  G06F16/28 ,  G06F16/9535 ,  G06F16/958

Abstract: Systems and methods provide for analyzing a group of online articles to identify relevant and popular online articles given a selection of topic(s) and/or term(s). An article score is generated for each online article based on the selected topic(s) and/or term(s) as a function of the relevance of the topic(s) and/or term(s) to the online article and visitor metrics for the online articles. The online articles are ranked based on the article scores, and an indication of the ranked online articles is provided for presentation to the user. In further embodiments, important terms are identified for a selection of topic(s) and/or term(s) based on the most relevant and popular online articles for the selected topics/terms.