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公开(公告)号：US20230325693A1
公开(公告)日：2023-10-12
申请号：US18194679
申请日：2023-04-03
申请人： INTUIT INC.
发明人： Grace WU , Shashank SHASHIKANT RAO , Susrutha GONGALLA , Ngoc Nhung HO , Carly WOOD , Vaibhav SHARMA
摘要： 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：US20190318031A1
公开(公告)日：2019-10-17
申请号：US15955345
申请日：2018-04-17
申请人： INTUIT INC.
发明人： 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分类号： G06F17/30 , G06N7/00 , G06F3/0485
摘要： 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.
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公开(公告)号：US20210124769A1
公开(公告)日：2021-04-29
申请号：US17141451
申请日：2021-01-05
申请人： INTUIT INC.
发明人： 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分类号： G06F16/28 , G06F3/0485 , G06N7/00
摘要： 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 provide input related to the pre-classified data set based on the summary. Embodiments further include receiving input from the user via the user interface, the input relating to the pre-classified data set.
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公开(公告)号：US20240144059A1
公开(公告)日：2024-05-02
申请号：US18409987
申请日：2024-01-11
申请人： INTUIT INC.
发明人： Grace WU , Shashank SHASHIKANT RAO , Susrutha GONGALLA , Nhung HO , Carly WOOD , Vaibhav SHARMA
摘要： 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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