公开(公告)号：US20240143641A1

公开(公告)日：2024-05-02

申请号：US18049958

申请日：2022-10-26

Applicant: SAP SE

Inventor： Lev Sigal ,  Anna Fishbein ,  Anton Ioffe ,  Iryna Butselan

IPC: G06F16/35 ,  G06N5/02

CPC classification number: G06F16/35 ,  G06N5/022

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program may receive a plurality of string data. The program may determine an embedding for each string data in the plurality of string data. The program may cluster the embeddings into groups of embeddings. The program may determine a plurality of labels for the plurality of string data based on the groups of embeddings. The program may use the plurality of labels and the plurality of string data to train a classifier model. The program may provide a particular string data as an input to the trained classifier model, wherein the classifier model is configured to determine, based on the particular string data, a classification for the particular string data.

公开(公告)号：US12266021B2

公开(公告)日：2025-04-01

申请号：US17732730

申请日：2022-04-29

Applicant: SAP SE

Inventor： Lev Sigal ,  Anna Fishbein ,  Anton Ioffe

IPC: G06Q40/12 ,  G06N3/048 ,  G06N3/10

Abstract: Systems and methods are provided for training a machine learning model to use comments entered by a user submitting an expense to determine a correct expense type. The trained machine learning model is used to predict an expense type by analyzing submitted text comments corresponding to a submitted expense. The expense can be flagged if a mismatch is determined between the expense type of the submitted expense and the predicted expense type, or the submitted expense can be automatically updated to the predicted expense type.

公开(公告)号：US12293601B2

公开(公告)日：2025-05-06

申请号：US17897022

申请日：2022-08-26

Applicant: SAP SE

Inventor： Lev Sigal ,  Anna Fishbein ,  Anton Ioffe ,  Iryna Butselan

IPC: G06V30/418 ,  G06V30/19 ,  G06V30/413

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives an image of a document, the document comprising a set of text. The program further provides the set of text to a machine learning model configured to determine, based on the set of text, a plurality of probabilities for a plurality of defined types of documents. Based on the plurality of probabilities for the plurality of defined types of documents, the program also determines a type of the document from the plurality of defined types of documents.

公开(公告)号：US20240071121A1

公开(公告)日：2024-02-29

申请号：US17897022

申请日：2022-08-26

Applicant: SAP SE

Inventor： Lev Sigal ,  Anna Fishbein ,  Anton Ioffe ,  Iryna Butselan

IPC: G06V30/418 ,  G06V30/19 ,  G06V30/413

CPC classification number: G06V30/418 ,  G06V30/19147 ,  G06V30/413

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives an image of a document, the document comprising a set of text. The program further provides the set of text to a machine learning model configured to determine, based on the set of text, a plurality of probabilities for a plurality of defined types of documents. Based on the plurality of probabilities for the plurality of defined types of documents, the program also determines a type of the document from the plurality of defined types of documents.

公开(公告)号：US20230351523A1

公开(公告)日：2023-11-02

申请号：US17732730

申请日：2022-04-29

Applicant: SAP SE

Inventor： Lev Sigal ,  Anna Fishbein ,  Anton Ioffe

IPC: G06Q40/00 ,  G06N3/04 ,  G06N3/10

CPC classification number: G06Q40/12 ,  G06N3/0481 ,  G06N3/10

Abstract: Systems and methods are provided for training a machine learning model to use comments entered by a user submitting an expense to determine a correct expense type. The trained machine learning model is used to predict an expense type by analyzing submitted text comments corresponding to a submitted expense. The expense can be flagged if a mismatch is determined between the expense type of the submitted expense and the predicted expense type, or the submitted expense can be automatically updated to the predicted expense type.