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公开(公告)号：US11797593B2
公开(公告)日：2023-10-24
申请号：US17855685
申请日：2022-06-30
申请人： Intuit Inc.
IPC分类号： G06F16/35 , G06F16/33 , G06F16/36 , G06F16/34 , G06F16/338
CPC分类号： G06F16/35 , G06F16/338 , G06F16/3331 , G06F16/34 , G06F16/36
摘要： The invention relates to a method for mapping topics. The method includes obtaining terms, obtaining tokens from each term, and identifying a first and a second set of topics. Each of the topics represents one or more of the terms. The method further includes identifying first and second topic names for the first and the second sets of topics. For each topic, the tokens associated with the terms assigned to the topic are analyzed for relevance, and a token with a high relevance is selected as the topic name. The method also includes selecting one of the first and one of the second sets of topics to obtain first and second selected topics, determining, based on the one or more terms, a similarity value between each of the first and the second selected topics, and establishing a mapping between similar first and second selected topics.
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公开(公告)号：US10860631B1
公开(公告)日：2020-12-08
申请号：US16014769
申请日：2018-06-21
申请人： INTUIT INC.
IPC分类号： G06F16/33 , G06F16/31 , G06F16/338 , G06F16/93
摘要： A processor may identify a combination term including at least two individual terms within at least one source of truth stored in a memory in communication with the processor. The processor may identify at least one document including the at least two of the individual search terms. The processor may determine a document weight for the at least one document based on the combination search term and the at least two of the individual search terms within the combination search term. The processor may provide the document as a search result arranged according to the document weight and/or may index the document according to the document weight.
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公开(公告)号：US20220277399A1
公开(公告)日：2022-09-01
申请号：US17187660
申请日：2021-02-26
申请人： Intuit Inc.
摘要： A method performs personalized transaction categorization. A transaction record is received, by a server application. In a first stage, sparse raw features are extracted from a transaction record of a transaction and converted into a transaction vector including dense features. In a second stage, the transaction vector is classified into a customized chart of accounts using the dense features to generate adapter model output. The method further includes selecting, an account identifier, corresponding to the transaction record and to an account of the customized chart of accounts, using the adapter model output, and presenting the account identifier for the transaction record.
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公开(公告)号：US20220335076A1
公开(公告)日：2022-10-20
申请号：US17855685
申请日：2022-06-30
申请人： Intuit Inc.
IPC分类号： G06F16/35 , G06F16/34 , G06F16/338 , G06F16/33
摘要： The invention relates to a method for mapping topics. The method includes obtaining terms, obtaining tokens from each term, and identifying a first and a second set of topics. Each of the topics represents one or more of the terms. The method further includes identifying first and second topic names for the first and the second sets of topics. For each topic, the tokens associated with the terms assigned to the topic are analyzed for relevance, and a token with a high relevance is selected as the topic name. The method also includes selecting one of the first and one of the second sets of topics to obtain first and second selected topics, determining, based on the one or more terms, a similarity value between each of the first and the second selected topics, and establishing a mapping between similar first and second selected topics.
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公开(公告)号：US20220318925A1
公开(公告)日：2022-10-06
申请号：US17218079
申请日：2021-03-30
申请人： Intuit Inc.
发明人： Lei Pei , Juan Liu , Ruobing Lu , Ying Sun , Heather Elizabeth Simpson , Nhung Ho
摘要： A method utilizes a framework for transaction categorization personalization. A transaction record is received. a baseline model is selected from a plurality of machine learning models. An account identifier, corresponding to the transaction record using the baseline model, is selected. The account identifier for the transaction record is presented.
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公开(公告)号：US10984340B2
公开(公告)日：2021-04-20
申请号：US15476647
申请日：2017-03-31
申请人： INTUIT INC.
发明人： Yu-Chung Hsiao , Lei Pei , Meng Chen , Nhung Ho
摘要： The present disclosure provides a composite machine-learning system for a transaction labeling service. A transaction labeling service receives at least one descriptive string describing a transaction associated with a user. The service identifies a preliminary grouping from a generalized scheme. The service extracts a set of N-grams from the descriptive string and converts the N-grams and the preliminary grouping into a set of features. A machine-learning model determines a label from a labeling scheme for the transaction based on the features. User input related to the label includes an accuracy indicator and a reliability indicator. If the reliability indicator satisfies a reliability condition, a set of training data for the machine-learning model is updated based on the descriptive string and the label. The machine-learning model is then trained against the updated set of training data.
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公开(公告)号：US11816544B2
公开(公告)日：2023-11-14
申请号：US17232455
申请日：2021-04-16
申请人： INTUIT INC.
发明人： Yu-Chung Hsiao , Lei Pei , Meng Chen , Nhung Ho
CPC分类号： G06N20/00 , G06N5/04 , G06N20/20 , G06Q30/04 , G06Q40/123
摘要： The present disclosure provides a composite machine learning system for a transaction labeling service. A transaction labeling service receives at least one descriptive string describing a transaction associated with a user. The service identifies a preliminary grouping from a generalized scheme. The service extracts a set of N-grams from the descriptive string and converts the N-grams and the preliminary grouping into a set of features. A machine learning model determines a label from a labeling scheme for the transaction based on the features. User input related to the label includes an accuracy indicator and a reliability indicator. If the reliability indicator satisfies a reliability condition, a set of training data for the machine learning model is updated based on the descriptive string and the label. The machine learning model is then trained against the updated set of training data.
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公开(公告)号：US11409778B2
公开(公告)日：2022-08-09
申请号：US17033598
申请日：2020-09-25
申请人： Intuit Inc.
IPC分类号： G06F16/35 , G06F16/33 , G06F16/338 , G06F16/34
摘要： A method including obtaining terms that are specific to a domain. First and second sets of the terms are obtained from first and second users. The first set do not adhere to a standard; the second terms do adhere to the standard. Tokens are obtained from the terms. First and second topics, representing terms, are identified within the domain. The terms are assigned to exactly one corresponding topic. The terms are assigned to the topics. First and second topic names are identified for the first and second topics. Identifying includes analyzing, for relevance, ones of the tokens. Identifying also includes selecting a particular token as a selected topic name for a selected one of the first topics and the second topics. A similarity value is determined between the first and the second selected topics. A mapping is established, based on the similarity value, between the first and second selected topic.
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公开(公告)号：US11182448B1
公开(公告)日：2021-11-23
申请号：US16526726
申请日：2019-07-30
申请人： INTUIT INC.
IPC分类号： G06F16/00 , G06F16/9536 , G06F16/9032 , G06N20/20
摘要： Certain aspects of the present disclosure provide techniques for determining content quality of a set of content item based on generating a score for each content item. An example technique includes using a trained content quality model to generate the score for each content item component. In such example, the model is trained using a calculated set of features associated with text and metadata of a content item in a training data set as well as a quality label for the content item. The model is trained by associating the set of features with the quality label for each content item in the training data.
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公开(公告)号：US20220318898A1
公开(公告)日：2022-10-06
申请号：US17217907
申请日：2021-03-30
申请人： Intuit Inc.
发明人： Lei Pei , Juan Liu , Ruobing Lu , Ying Sun , Heather Elizabeth Simpson , Nhung Ho
摘要： A method categorizes transaction records. A transaction record is received by a server application. The transaction record is encoded with a first machine learning model to obtain a transaction vector, wherein the transaction vector is in a same vector space as multiple account vectors. A second machine learning model executing in the server application, selects an account vector, from the multiple account vectors, corresponding to the transaction vector. An account identifier, corresponding to the account vector, is presented for the transaction record.
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