公开(公告)号：US11816687B2

公开(公告)日：2023-11-14

申请号：US16916915

申请日：2020-06-30

Applicant: INTUIT INC.

Inventor： Juan Liu ,  Ying Yang ,  Amrita Damani ,  David Joseph Antestenis ,  Aaron Dibner-Dunlap ,  Grace Wu

IPC: G06Q30/0202 ,  G06N20/20 ,  G06N5/04 ,  G06N7/01 ,  G06N5/01

CPC classification number: G06Q30/0202 ,  G06N20/20 ,  G06N5/01 ,  G06N5/04 ,  G06N7/01

Abstract: Dynamic state-space modeling within a special purpose hardware platform to determine non-conversion risks for each trial user and churn risks for each active subscriber having exhibited a sequence of behaviors. The state-space model may be operable to determine a loss risk for each of a provider's active trial users and/or subscribers.

公开(公告)号：US11645564B2

公开(公告)日：2023-05-09

申请号：US17404356

申请日：2021-08-17

Applicant: INTUIT INC.

Inventor： Grace Wu ,  Shashank Shashikant Rao ,  Susrutha Gongalla ,  Ngoc Nhung Ho ,  Carly Wood ,  Vaibhav Sharma

IPC: G06Q10/04 ,  G06N5/048

CPC classification number: G06N5/048 ,  G06Q10/04

Abstract: Aspects of the present disclosure provide techniques for classifying a trip. Embodiments include receiving, from a plurality of users, a plurality of historical trip records. Each of the plurality of historical trip records may comprise one or more historical trip attributes and historical classification information. Embodiments include training a predictive model, using the plurality of historical trip records, to classify trips based on trip records. Training the predictive model may comprise determining a plurality of hot spots based on the historical trip records, each of the plurality of hot spots comprising a region encompassing one or more locations, and associating, in the predictive model, the plurality of hot spots with historical classification information. Embodiments include receiving, from a user, a new trip record comprising a plurality of trip attributes related to a trip and using the predictive model to predict a classification for the trip based on the trip record.

公开(公告)号：US20190295158A1

公开(公告)日：2019-09-26

申请号：US15935997

申请日：2018-03-26

Applicant: INTUIT INC.

Inventor： Grace Wu

IPC: G06Q40/02 ,  H04W4/029 ,  H04L29/08

Abstract: Certain aspects of the present disclosure provide techniques for predicting a transaction time based on user position data. In certain aspects, a method for predicting a transaction time based on user position data includes obtaining a transaction record and one or more user positions associated with a user. The method also includes obtaining one or more business records associated with each respective user position. The method further includes calculating one or more similarity scores, where each similarity score is based on a similarity between a respective business record and the transaction record. The method also includes associating the transaction record with a business record based on a maximum similarity score of the one or more similarity scores. The method further includes determining a predicted transaction time for the transaction record based on at least a timestamp of a user position associated with the business record associated with the transaction record.

公开(公告)号：US11429881B1

公开(公告)日：2022-08-30

申请号：US16510195

申请日：2019-07-12

Applicant: INTUIT INC.

Inventor： Grace Wu ,  Shashank Shashikant Rao ,  Susrutha Gongalla ,  Ngoc Nhung Ho

IPC: G06N20/00 ,  G06F16/28 ,  G06N5/04 ,  G06F9/451

Abstract: Certain aspects of the present disclosure provide techniques for providing personalized groups of travel data for review through a user interface. Embodiments include receiving trip records associated with a user from an application running on a remote device, providing the trip records to a prediction model, and receiving a plurality of groups from the prediction model, each group of the plurality of groups comprising a subset of the trip records. Embodiments include providing each group of the plurality of groups to a personalization model, the personalization model having been trained based on user feedback to determine personalization scores for each group of the plurality of groups. Embodiments include receiving a personalization score for each group of the plurality of groups from the personalization model and transmitting one or more groups selected based on the personalization scores to the application to be displayed via the user interface.

公开(公告)号：US11276112B2

公开(公告)日：2022-03-15

申请号：US15935997

申请日：2018-03-26

Applicant: INTUIT INC.

Inventor： Grace Wu

IPC: G06Q40/02 ,  H04L67/50 ,  H04W4/029

Abstract: Certain aspects of the present disclosure provide techniques for predicting a transaction time based on user position data. In certain aspects, a method for predicting a transaction time based on user position data includes obtaining a transaction record and one or more user positions associated with a user. The method also includes obtaining one or more business records associated with each respective user position. The method further includes calculating one or more similarity scores, where each similarity score is based on a similarity between a respective business record and the transaction record. The method also includes associating the transaction record with a business record based on a maximum similarity score of the one or more similarity scores. The method further includes determining a predicted transaction time for the transaction record based on at least a timestamp of a user position associated with the business record associated with the transaction record.

公开(公告)号：US10909147B2

公开(公告)日：2021-02-02

申请号：US15955345

申请日：2018-04-17

Applicant: INTUIT INC.

Inventor： Joanna Sim ,  Hannah Hudson ,  Rit Mishra ,  Justin Calles ,  Prasannavenkatesh Chandrasekar ,  Carly Wood ,  Grace Wu ,  Susrutha Gongalla ,  Heidi Yang ,  Gerald Carvalho ,  Justin Li ,  Catherine Cacheris

IPC: G06F16/00 ,  G06F16/28 ,  G06F3/0485 ,  G06N7/00

Abstract: Aspects of the present disclosure provide techniques for displaying reduced data sets based on pre-classification of a larger data set. Embodiments include receiving a plurality of activity records describing a plurality of activities associated with the user. Embodiments further include grouping the plurality of activities into one or more pre-classified data sets based on the plurality of activity records. Embodiments further include providing the user with a summary of a pre-classified data set of the one or more pre-classified data sets via a user interface. Embodiments further include providing the user, via the user interface, with a user interface element that allows the user to categorize all activities in the pre-classified data set together based on the summary. Embodiments further include receiving input from the user via the user interface, the input assigning a category to all activities in the pre-classified data set together based on the summary.

公开(公告)号：US11797891B1

公开(公告)日：2023-10-24

申请号：US18049286

申请日：2022-10-24

Applicant: INTUIT INC.

Inventor： Yashwanth Musiboyina ,  Dawn-Marie Chantel Miesner ,  Mustapha Harb ,  Nan Jiang ,  Shahram Mohrehkesh ,  Zachary Dorsch ,  Suman Sundaresh ,  Grace Wu

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: The instant systems and methods are directed to a contextual bandits machine learning model configured to enable granular synchronized ecosystem personalization and optimization. The system and methods determine an objective and feed the objective and one more lifecycle model propensity scores as inputs to the contextual bandits machine learning model. The contextual bandits machine learning model then generates one or more potential weighted model rewards, wherein each potential weighted model reward includes at least a desired user action, a weight, a channel, and an expected change to the objective, and selects a weighted model reward that optimizes the objective. An action recommendation is subsequently transmitted to a user device based on the weighted model reward, wherein the action recommendation is presented in a selected channel associated with the weighted model reward. Feedback associated with the action recommendation is collected and used in training and fine-tuning of the model.

公开(公告)号：US11625737B2

公开(公告)日：2023-04-11

申请号：US16916930

申请日：2020-06-30

Applicant: INTUIT INC.

Inventor： Juan Liu ,  Ying Yang ,  Amrita Damani ,  David Joseph Antestenis ,  Aaron Dibner-Dunlap ,  Grace Wu

IPC: G06Q30/0202 ,  G06Q30/0201 ,  G06N20/00 ,  H04L51/04 ,  G06N3/02

Abstract: Predictive modeling within a special purpose hardware platform to determine scenarios that are most likely to increase conversion potential for each trial user and retention potential for each active subscriber of a service, collectively referred to as a propensity score. The predictive models are integrated with a contextual marketing system that uses a loss risk assessment to learn user behavior and optimize content messaging designed to improve actual conversion or retention behavior for the user.

公开(公告)号：US20220067560A1

公开(公告)日：2022-03-03

申请号：US17404356

申请日：2021-08-17

Applicant: INTUIT, INC.

Inventor： Grace Wu ,  Shashank Shashikant Rao ,  Susrutha Gongalla ,  Ngoc Nhung Ho ,  Carly Wood ,  Vaibhav Sharma

IPC: G06N5/04 ,  G06Q10/04

Abstract: Aspects of the present disclosure provide techniques for classifying a trip. Embodiments include receiving, from a plurality of users, a plurality of historical trip records. Each of the plurality of historical trip records may comprise one or more historical trip attributes and historical classification information. Embodiments include training a predictive model, using the plurality of historical trip records, to classify trips based on trip records. Training the predictive model may comprise determining a plurality of hot spots based on the historical trip records, each of the plurality of hot spots comprising a region encompassing one or more locations, and associating, in the predictive model, the plurality of hot spots with historical classification information. Embodiments include receiving, from a user, a new trip record comprising a plurality of trip attributes related to a trip and using the predictive model to predict a classification for the trip based on the trip record.

公开(公告)号：US11120349B1

公开(公告)日：2021-09-14

申请号：US15913812

申请日：2018-03-06

Applicant: INTUIT INC.

Inventor： Grace Wu ,  Shashank Shashikant Rao ,  Susrutha Gongalla ,  Ngoc Nhung Ho ,  Carly Wood ,  Vaibhav Sharma

IPC: G06N5/04 ,  G06Q10/04

Abstract: Aspects of the present disclosure provide techniques for classifying a trip. Embodiments include receiving, from a plurality of users, a plurality of historical trip records. Each of the plurality of historical trip records may comprise one or more historical trip attributes and historical classification information. Embodiments include training a predictive model, using the plurality of historical trip records, to classify trips based on trip records. Training the predictive model may comprise determining a plurality of hot spots based on the historical trip records, each of the plurality of hot spots comprising a region encompassing one or more locations, and associating, in the predictive model, the plurality of hot spots with historical classification information. Embodiments include receiving, from a user, a new trip record comprising a plurality of trip attributes related to a trip and using the predictive model to predict a classification for the trip based on the trip record.