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公开(公告)号：US11886515B2
公开(公告)日：2024-01-30
申请号：US17901648
申请日：2022-09-01
IPC分类号： G06F7/00 , G06F16/906 , G06F16/93 , G06F16/901
CPC分类号： G06F16/906 , G06F16/9024 , G06F16/93
摘要： Aspects of the present disclosure provide systems, methods, apparatus, and computer-readable storage media for extracting taxonomies based on hierarchical clustering on graphs related to a corpus of documents and using said taxonomies for classifying and labeling documents. The hierarchical clustering of graphs include the adaptive pruning of nodes at each hierarchy based on betweenness centrality of nodes to form clusters that have modularity score exceeding a minimum modularity threshold.
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公开(公告)号：US20210026823A1
公开(公告)日：2021-01-28
申请号：US17068818
申请日：2020-10-12
发明人： David von Rickenbach , David Oliver , Daniella Tsar , Kim Hau , Dorcas Mbwiti , Johannes Schleith , Guillaume Mosching , Sanzio Monti
摘要： The present disclosure relates to systems and methods for enhanced mapping of transaction data to a target document, and for classifying line items of the mapped transaction data, using classification algorithms. Embodiments provide a system including a column mapping module to receive a target scheme specifying a target structure for the target document, receive transaction data having a source structure, and map at least one source column to at least one target column of the target columns based on application of classification algorithms to features identified from the source transaction data. The system also includes a row classification module to classify the rows of the mapped transaction data into classification categories. The system also includes a validation handler to receive validation input from a user, validating the column mapping and/or the row classification. The validating including accepting the recommendation or rejecting the recommendation and selecting a correct choice.
101064083.1-
公开(公告)号：US20240168999A1
公开(公告)日：2024-05-23
申请号：US18426903
申请日：2024-01-30
IPC分类号： G06F16/906 , G06F16/901 , G06F16/93
CPC分类号： G06F16/906 , G06F16/9024 , G06F16/93
摘要： Aspects of the present disclosure provide systems, methods, apparatus, and computer-readable storage media for extracting taxonomies based on hierarchical clustering on graphs related to a corpus of documents and using said taxonomies for classifying and labeling documents. The hierarchical clustering of graphs include the adaptive pruning of nodes at each hierarchy based on betweenness centrality of nodes to form clusters that have modularity score exceeding a minimum modularity threshold.
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公开(公告)号：US11797503B2
公开(公告)日：2023-10-24
申请号：US17068818
申请日：2020-10-12
发明人： David von Rickenbach , David Oliver , Daniella Tsar , Kim Hau , Dorcas Mbwiti , Johannes Schleith , Guillaume Mosching , Sanzio Monti
CPC分类号： G06F16/22 , G06F11/0727 , G06F11/0793 , G06F16/285 , G06N7/01 , G06N20/00 , G06Q40/12
摘要： The present disclosure relates to systems and methods for enhanced mapping of transaction data to a target document, and for classifying line items of the mapped transaction data, using classification algorithms. Embodiments provide a system including a column mapping module to receive a target scheme specifying a target structure for the target document, receive transaction data having a source structure, and map at least one source column to at least one target column of the target columns based on application of classification algorithms to features identified from the source transaction data. The system also includes a row classification module to classify the rows of the mapped transaction data into classification categories. The system also includes a validation handler to receive validation input from a user, validating the column mapping and/or the row classification. The validating including accepting the recommendation or rejecting the recommendation and selecting a correct choice.
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公开(公告)号：US10803033B2
公开(公告)日：2020-10-13
申请号：US16181680
申请日：2018-11-06
发明人： David von Rickenbach , David Oliver , Daniella Tsar , Kim Hau , Dorcas Mbwiti , Johannes Schleith , Guillaume Mosching , Sanzio Monti
摘要： The present disclosure relates to systems and methods for enhanced mapping of transaction data to a target document, and for classifying line items of the mapped transaction data, using classification algorithms. Embodiments provide a system including a column mapping module to receive a target scheme specifying a target structure for the target document, receive transaction data having a source structure, and map at least one source column to at least one target column of the target columns based on application of classification algorithms to features identified from the source transaction data. The system also includes a row classification module to classify the rows of the mapped transaction data into classification categories. The system also includes a validation handler to receive validation input from a user, validating the column mapping and/or the row classification. The validating including accepting the recommendation or rejecting the recommendation and selecting a correct choice.
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