公开(公告)号：US20230289696A1

公开(公告)日：2023-09-14

申请号：US17693778

申请日：2022-03-14

Applicant: ADOBE INC.

Inventor： Arpit Ajay Narechania ,  Fan Du ,  Atanu R. Sinha ,  Ryan A. Rossi ,  Jane Elizabeth Hoffswell ,  Shunan Guo ,  Eunyee Koh ,  John Anderson ,  Sonali Surange ,  Saurabh Mahapatra ,  Vasanthi Holtcamp

IPC: G06Q10/06

CPC classification number: G06Q10/06393 ,  G06F3/0482

Abstract: Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: “quality”—the condition of data (e.g., presence of incorrect or incomplete values), its “consumption”—the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility”—a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle. For example, an interactive tree view may visually represent a nested attribute schema and attribute quality or consumption metrics to facilitate discovery of bad data before ingesting into a data lake.

公开(公告)号：US11665073B2

公开(公告)日：2023-05-30

申请号：US17319364

申请日：2021-05-13

Applicant: Adobe Inc.

Inventor： Pranav Ravindra Maneriker ,  Reshmi Sasidharan ,  Atanu R. Sinha

IPC: H04L43/0823 ,  H04L41/14 ,  H04L41/22

CPC classification number: H04L43/0823 ,  H04L41/14 ,  H04L41/22

Abstract: In some embodiments, an intervention evaluation system estimates counterfactual metric for a focal online platform based on an assessment model built using performance data of the focal online platform and control online platforms. The intervention evaluation system accesses performance data of the focal online platform that has been subject to a temporary intervention and performance data of control online platforms that are not subject to the temporary intervention. The intervention evaluation system determines estimation weights for these control online platforms based on the performance data in a pre-intervention period. Based on the estimation weights, the intervention evaluation system computes a counterfactual metric indicating the performance of the focal online platform in a post-intervention period in the absence of the temporary intervention. The counterfactual metric is transmitted to the focal online platform, where the counterfactual metric is usable for modifying an interactive computing environment provided by the focal online platform.

公开(公告)号：US20210266245A1

公开(公告)日：2021-08-26

申请号：US17319364

申请日：2021-05-13

Applicant: Adobe Inc.

Inventor： Pranav Ravindra Maneriker ,  Reshmi Sasidharan ,  Atanu R. Sinha

IPC: H04L12/26 ,  H04L12/24

Abstract: In some embodiments, an intervention evaluation system estimates counterfactual metric for a focal online platform based on an assessment model built using performance data of the focal online platform and control online platforms. The intervention evaluation system accesses performance data of the focal online platform that has been subject to a temporary intervention and performance data of control online platforms that are not subject to the temporary intervention. The intervention evaluation system determines estimation weights for these control online platforms based on the performance data in a pre-intervention period. Based on the estimation weights, the intervention evaluation system computes a counterfactual metric indicating the performance of the focal online platform in a post-intervention period in the absence of the temporary intervention. The counterfactual metric is transmitted to the focal online platform, where the counterfactual metric is usable for modifying an interactive computing environment provided by the focal online platform.

公开(公告)号：US11093957B2

公开(公告)日：2021-08-17

申请号：US15819808

申请日：2017-11-21

Applicant: Adobe Inc.

Inventor： Atanu R. Sinha ,  Meghanath Macha Yadagiri ,  Pranav Ravindra Maneriker ,  Sopan Khosla ,  Avani Samdariya ,  Navjot Singh

IPC: G06Q30/02 ,  G06Q10/06

Abstract: Modifications to the DiD technique are disclosed which provide an estimate of the effectiveness of a site-wide action where no control group exists within the data subsequent to implementation of the site-wide action. In some examples, a method may include identifying a treatment group based on a modified treatment period, selecting a control group from a control period prior to the modified treatment period, and performing a modified difference-in-differences (DiD) estimation for a metric based on the modified treatment period, the treatment group, the control period, and the control group. The modified treatment period may encompass an intervention of a site-wide action, and include a pre-intervention time period and a post-intervention time period.

公开(公告)号：US20210192549A1

公开(公告)日：2021-06-24

申请号：US16722626

申请日：2019-12-20

Applicant: Adobe Inc.

Inventor： Atanu R. Sinha ,  Paridhi Maheshwari ,  Ayalur Vedpuriswar Lakshmy ,  Tanay Anand ,  Vishal Manohar Jain

IPC: G06Q30/02

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for easily, accurately, and efficiently determining a personalized market share of a user with a company versus that of its competitors using only focal company's own clickstream data. For instance, the disclosed systems can infer a mapping of purchases to product categories from clickstream data of a company and use the mappings to generate a dataset of observable conversions (with interconversion times) for one or more product categories. Then, the disclosed systems can utilize models for a category level interconversion time and for transition probabilities of a user to determine a personalized market share and an interconversion time for an individual user (between the company and competitors of the company). In addition, the disclosed systems can generate graphical user interfaces that efficiently provide personalized customer statistics based at least on the determined personalized market share and interconversion times for the individual user.

公开(公告)号：US11023819B2

公开(公告)日：2021-06-01

申请号：US15946884

申请日：2018-04-06

Applicant: Adobe Inc.

Inventor： Atanu R. Sinha ,  Deepali Jain ,  Nikhil Sheoran ,  Deepali Gupta ,  Sopan Khosla

IPC: G06N7/00 ,  G06N20/00 ,  G06K9/62 ,  G06F17/11

Abstract: In some embodiments, a computing system computes, with a state prediction model, probabilities of transitioning from a click state represented by interaction data to various predicted next states. The computing system computes an interface experience metric for the click with an experience valuation model. To do so, the computing system identifies base values for the click state and the predicted next states. The computing system computes value differentials for between the click state's base value and each predicted next state's base value. Value differentials indicate qualities of interface experience. The computing system determines the interface experience metric from a summation that includes the current click state's base value and the value differentials weighted with the predicted next states' probabilities. The computing system transmits the interface experience metric to an online platform, which can cause interface elements of the online platform to be modified based on the interface experience metric.

公开(公告)号：US10311913B1

公开(公告)日：2019-06-04

申请号：US15902046

申请日：2018-02-22

Applicant: Adobe Inc.

Inventor： Sumit Shekhar ,  Harvineet Singh ,  Dhruv Singal ,  Atanu R. Sinha

IPC: G11B27/031 ,  G06K9/00 ,  G06K9/62

Abstract: Certain embodiments involve generating summarized versions of video content based on memorability of the video content. For example, a video summarization system accesses segments of an input video. The video summarization system identifies memorability scores for the respective segments. The video summarization system selects a subset of segments from the segments based on each computed memorability score in the subset having a threshold memorability score. The video summarization system generates visual summary content from the subset of the segments.

公开(公告)号：US20190156359A1

公开(公告)日：2019-05-23

申请号：US15819808

申请日：2017-11-21

Applicant: Adobe Inc.

Inventor： Atanu R. Sinha ,  Meghanath Macha Yadagiri ,  Pranav Ravindra Maneriker ,  Sopan Khosla ,  Avani Samdariya ,  Navjot Singh

IPC: G06Q30/02 ,  G06Q10/06

Abstract: Modifications to the DiD technique are disclosed which provide an estimate of the effectiveness of a site-wide action where no control group exists within the data subsequent to implementation of the site-wide action. In some examples, a method may include identifying a treatment group based on a modified treatment period, selecting a control group from a control period prior to the modified treatment period, and performing a modified difference-in-differences (DiD) estimation for a metric based on the modified treatment period, the treatment group, the control period, and the control group. The modified treatment period may encompass an intervention of a site-wide action, and include a pre-intervention time period and a post-intervention time period.

公开(公告)号：US20250061488A1

公开(公告)日：2025-02-20

申请号：US18451590

申请日：2023-08-17

Applicant: ADOBE INC.

Inventor： Atanu R. Sinha ,  Ryan A. Rossi ,  Sunav Choudhary ,  Harshita Chopra ,  Paavan Indela ,  Veda Pranav Parwatala ,  Srinjayee Paul ,  Saurabh Mahapatra ,  Aurghya Maiti

IPC: G06Q30/0251 ,  G06N20/00 ,  G06Q30/0204

Abstract: Systems and methods for delivery aware audience segmentation and subsequent delivery of content are described. Embodiments are configured to obtain activity data for a user, assign the user to a user segment based on the activity data using a machine learning model, generate a reach prediction for the user segment, select a media channel for communicating with the user based on the user segment and the reach prediction, and provide targeted content to the user via the selected media channel. According to some aspects, the machine learning model is trained based on content reach data.

公开(公告)号：US20240232775A9

公开(公告)日：2024-07-11

申请号：US17969643

申请日：2022-10-19

Applicant: Adobe Inc.

Inventor： Atanu R. Sinha ,  Shiv Kumar Saini ,  Prithvi Bhutani ,  Nikhil Sheoran ,  Kevin Cobourn ,  Jeff D. Chasin ,  Fan Du ,  Eric Matisoff

IPC: G06Q10/0639 ,  G06F3/0484

CPC classification number: G06Q10/06393 ,  G06F3/0484

Abstract: In some examples, an environment evaluation system accesses interaction data recording interactions by users with an online platform hosted by a host system and computes, based on the interaction data, interface experience metrics. The interface experience metrics includes an individual experience metric for each user and a transition experience metric for each transition in the interactions by the users with the online platform. The environment evaluation system identifies a user with the individual experience metric below a pre-determined threshold, identifies a transition performed by the user that has a transition experience metric below a second threshold, and analyzes the transition to determine users who have performed the transition. The environment evaluation system updates the host system with the individual experience metrics and the transition metrics, based on which the host system can perform modifications of interface elements of the online platform to improve the experience.