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1.发明申请公开(公告)号：US20220351002A1
公开(公告)日：2022-11-03
申请号：US17862494
申请日：2022-07-12
Applicant: Intuit Inc.
Inventor： Sambarta Dasgupta , Sricharan Kallur Palli Kumar , Shashank Shashikant Rao , Colin R. Dillard
Abstract: Systems and methods for forecasting cashflows across one or more accounts of a user disclosed. One example method may include retrieving a data set for each of a plurality of accounts from a database, constructing a graph including a plurality of nodes linked together by a multitude of edges, wherein each node identifies a time series value corresponding to one of the accounts, and each edge indicates a time series value of a corresponding set of transactions occurring between a corresponding pair of accounts, determining a plurality of constraints, determining a specified loss function based on the plurality of constraints, back-propagating a derivative of the specified loss function into a deep neural network (DNN) to determine a set of neural network parameters, forecasting, using the DNN, a time sequence for one or more of the nodes and one or more of the edges, and providing the forecasted time sequences to the user.
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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
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.
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公开(公告)号：US11922208B1
公开(公告)日：2024-03-05
申请号：US18326255
申请日：2023-05-31
Applicant: Intuit Inc.
Inventor： Immanuel David Buder , Shashank Shashikant Rao
IPC: G06F9/48
CPC classification number: G06F9/48
Abstract: Systems and methods are disclosed for switching between batch processing and real-time processing of time series data, with a system being configured to switch between a batch processing module and a real-time processing module to process time series data. The system includes an orchestration service to indicate when to switch, which may be based on a switching event identified by the orchestration service. In some implementations, the orchestration service identifies a switching event in incoming time series data to be processed. When a batch processing module is to be used to batch process time series data, the real-time processing module may be disabled, with the real-time processing module being enabled when it is used to process the time series data. In some implementations, the real-time processing module includes the same processing models as the batch processing module such that the two modules' outputs have a similar accuracy.
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公开(公告)号：US11663493B2
公开(公告)日：2023-05-30
申请号：US16262208
申请日：2019-01-30
Applicant: Intuit Inc.
Inventor： Shashank Shashikant Rao , Sambarta Dasgupta , Colin Dillard
CPC classification number: G06N3/126 , G06F16/285 , G06N5/04
Abstract: Forecasts are provided based on dynamic model selection for different sets of time series. A model comprises a transformation and a prediction algorithm. Given a time series, a transformation is selected for the time series and a prediction algorithm is selected to make a forecast based on the transformed time series. Sets of time series are distinguished from each other based on diverse sparsities, temporal scales and other time series attributes. A model is dynamically selected based on time series attributes to increase forecasting accuracy and decrease forecasting computation time. The dynamic model selection is based on the creation of a meta-model from historical sets of historical time series.
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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
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.
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Patent Agency Ranking
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
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.
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公开(公告)号：US11657302B2
公开(公告)日：2023-05-23
申请号：US16688945
申请日：2019-11-19
Applicant: Intuit Inc.
Inventor： Sambarta Dasgupta , Colin R. Dillard , Shashank Shashikant Rao
IPC: G06F16/24 , G06N5/04 , G06F16/2455 , G06N3/126
CPC classification number: G06N5/04 , G06F16/24568 , G06N3/126
Abstract: Systems and methods for forecasting future values of data streams are disclosed. One example method may include receiving information characterizing each of a plurality of forecasting models, retrieving historical data for each of a plurality of data streams, determining one or more constraints, dynamically selecting one of the plurality of forecasting models for each of the data streams based on accuracy metrics for the forecasting models, estimating cost metrics associated with each forecasting model, dynamically selecting the forecasting model based at least in part on the accuracy metrics, the cost metrics, and the determined constraints, and forecasting a first subsequent value of each data stream using the corresponding selected forecasting model.
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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
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.
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9.发明授权公开(公告)号：US11423250B2
公开(公告)日：2022-08-23
申请号：US16688927
申请日：2019-11-19
Applicant: Intuit Inc.
Inventor： Sambarta Dasgupta , Sricharan Kallur Palli Kumar , Shashank Shashikant Rao , Colin R. Dillard
Abstract: Systems and methods for forecasting cashflows across one or more accounts of a user disclosed. One example method may include retrieving a data set for each of a plurality of accounts from a database, constructing a graph including a plurality of nodes linked together by a multitude of edges, wherein each node identifies a time series value corresponding to one of the accounts, and each edge indicates a time series value of a corresponding set of transactions occurring between a corresponding pair of accounts, determining a plurality of constraints, determining a specified loss function based on the plurality of constraints, back-propagating a derivative of the specified loss function into a deep neural network (DNN) to determine a set of neural network parameters, forecasting, using the DNN, a time sequence for one or more of the nodes and one or more of the edges, and providing the forecasted time sequences to the user.
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10.发明申请公开(公告)号：US20210150259A1
公开(公告)日：2021-05-20
申请号：US16688927
申请日：2019-11-19
Applicant: Intuit Inc.
Inventor： Sambarta Dasgupta , Sricharan Kallur Palli Kumar , Shashank Shashikant Rao , Colin R. Dillard
Abstract: Systems and methods for forecasting cashflows across one or more accounts of a user disclosed. One example method may include retrieving a data set for each of a plurality of accounts from a database, constructing a graph including a plurality of nodes linked together by a multitude of edges, wherein each node identifies a time series value corresponding to one of the accounts, and each edge indicates a time series value of a corresponding set of transactions occurring between a corresponding pair of accounts, determining a plurality of constraints, determining a specified loss function based on the plurality of constraints, back-propagating a derivative of the specified loss function into a deep neural network (DNN) to determine a set of neural network parameters, forecasting, using the DNN, a time sequence for one or more of the nodes and one or more of the edges, and providing the forecasted time sequences to the user.
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