公开(公告)号：US12100007B2

公开(公告)日：2024-09-24

申请号：US17900535

申请日：2022-08-31

Applicant: COUPA SOFTWARE INCORPORATED

Inventor： Kiran Ratnapu ,  Prasanna Kumar ,  Mikin Faldu ,  Fang Chang ,  Maggie M Joy ,  Arjun Ramaratnam ,  Amit Vijayant

IPC: G06Q20/40 ,  G06Q30/0204

CPC classification number: G06Q20/4016 ,  G06Q30/0204

Abstract: Computer-implemented techniques for repeatable and interpretable divisive analysis. In one embodiment, for example, a method comprises: identifying top-level cohorts of data items based on one or more characteristics of the data items in common; recursively or iteratively dividing a selected top-level cohort in a top-down manner resulting in a plurality of sub-level cohorts arranged in a hierarchy; detecting a particular data item that is a statistical outlier among data items of a leaf cohort in the hierarchy; and causing display of an indication in a computer user interface that the particular data item is an outlier.

公开(公告)号：US20200043006A1

公开(公告)日：2020-02-06

申请号：US16419438

申请日：2019-05-22

Applicant: Coupa Software Incorporated

Inventor： Kiran Ratnapu ,  Prasanna Kumar ,  Mikin Faldu ,  Fang Chang ,  Maggie M. Joy ,  Arjun Ramaratnam ,  Amit Vijayant

IPC: G06Q20/40

Abstract: Computer-implemented techniques for repeatable and interpretable divisive analysis. In one embodiment, for example, a method comprises: identifying top-level cohorts of data items based on one or more characteristics of the data items in common; recursively or iteratively dividing a selected top-level cohort in a top-down manner resulting in a plurality of sub-level cohorts arranged in a hierarchy; detecting a particular data item that is a statistical outlier among data items of a leaf cohort in the hierarchy; and causing display of an indication in a computer user interface that the particular data item is an outlier.

公开(公告)号：US20240264989A1

公开(公告)日：2024-08-08

申请号：US18427309

申请日：2024-01-30

Applicant: Coupa Software Incorporated

Inventor： Jyotirmaya Mahanta ,  Ankit Narang ,  Shoan Jain ,  Prasanna Kumar

IPC: G06F16/215 ,  G06V30/19 ,  G06V30/412

CPC classification number: G06F16/215 ,  G06V30/19093 ,  G06V30/412

Abstract: A computer-implemented method is disclosed. The method includes obtaining, by a de-duplication server, a candidate pair of a plurality of digitally stored documents from a document database. Text elements are identified from each digitally stored document in the candidate pair in response, and the text elements are stored as document extraction attributes. The method then automatically computes and stores relative positional differences of the text elements between each digitally stored document of the candidate pair and a document similarity score based on the relative positional differences. The relative positional differences are compared with a similarity function to form a difference similarity vector for the candidate pair. The difference similarity vector comprises components corresponding to each relative positional difference. The components of the difference similarity vector are aggregated to determine a final score for the candidate pair. A document-level similarity metric is determined from the final score. The method includes determining whether the final score is above a cutoff value, and in response to determining that the final score for the candidate pair is above the cutoff value, comparing the document extraction attribute with the final score. The method also determines whether the document-level similarity metric is above a threshold value by the de-duplication server. The candidate pair is classified based on determining that the document-level similarity metric is above the threshold value to de-duplicate the plurality of digitally stored documents in the candidate pair. Based on the classifying, duplicate transaction documents are removed from the document database by any of deleting records, marking records, updating column attributes, or writing records to a different table.

公开(公告)号：US11587144B1

公开(公告)日：2023-02-21

申请号：US17496149

申请日：2021-10-07

Applicant: Coupa Software Incorporated

Inventor： Scott Harris ,  Vincent Toesca ,  Prasanna Kumar ,  Amit Vijayant

IPC: G06Q30/00 ,  G06Q30/0601 ,  G06Q30/0201

Abstract: A method and apparatus for generating recommendation data for cataloging items in an e-procurement system is provided. In various embodiments, a database of records is created and maintained corresponding to a plurality of transactions in an e-procurement system. In various embodiments, database records are weighted and sorted according a transaction method associated with the records. In various embodiments, recommendation data is generated for items associated with the records to suggest more efficient methods for offering items for procurement in an e-marketplace based on the weights and sort order of the records.

公开(公告)号：US11188966B1

公开(公告)日：2021-11-30

申请号：US16563615

申请日：2019-09-06

Applicant: Coupa Software Incorporated

Inventor： Scott Harris ,  Vincent Toesca ,  Prasanna Kumar ,  Amit Vijayant

IPC: G06Q30/00 ,  G06Q30/06 ,  G06Q30/02

Abstract: A method and apparatus for generating recommendation data for cataloging items in an e-procurement system is provided. In various embodiments, a database of records is created and maintained corresponding to a plurality of transactions in an e-procurement system. In various embodiments, database records are weighted and sorted according a transaction method associated with the records. In various embodiments, recommendation data is generated for items associated with the records to suggest more efficient methods for offering items for procurement in an e-marketplace based on the weights and sort order of the records.

公开(公告)号：US20200380455A1

公开(公告)日：2020-12-03

申请号：US16676391

申请日：2019-11-06

Applicant: Coupa Software Incorporated

Inventor： Maggie Mae Joy ,  Daniel Benson ,  Fang-Kuey Chang ,  Kiran Ratnapu ,  Ankit Narang ,  Shoan Jain ,  Raghunandan Somaraju ,  Prasanna Kumar ,  Angela Welchel ,  Mikin Faldu ,  Dipeshkumar Vasantbhai Prajapati ,  Ketan Vasantkumar Darji ,  Rucha Apte

IPC: G06Q10/08 ,  G06N20/00

Abstract: Systems and methods for improving a computing system comparing past post-approved transaction records to past pre-approved transaction records are described herein. In an embodiment, a server stores a first plurality of digital electronic records identifying a plurality of past post-approved transactions by a first entity and a second plurality of digital electronic records for the first entity identifying a plurality of past pre-approved transactions by the first entity. The server uses a first machine learning system to determine that a subset of the first plurality of digital electronic records which identify a subset of the plurality of past post-approved transactions correspond to one or more pre-identified categories and a second machine learning system to match one or more particular digital electronic records of the subset of the first plurality of digital electronic records with one or more records of the second plurality of digital electronic records.

公开(公告)号：US20220405701A1

公开(公告)日：2022-12-22

申请号：US17893768

申请日：2022-08-23

Applicant: Coupa Software Incorporated

Inventor： Maggie Mae Joy ,  Daniel Benson ,  Fang-Kuey Chang ,  Kiran Ratnapu ,  Ankit Narang ,  Shoan Jain ,  Raghunandan Somaraju ,  Prasanna Kumar ,  Angela Welchel ,  Mikin Faldu ,  Dipeshkumar Vasantbhai Prajapati ,  Ketan Vasantkumar Darji ,  Rucha Apte

IPC: G06Q10/08 ,  G06N20/00

Abstract: Systems and methods for improving a computing system comparing past post-approved transaction records to past pre-approved transaction records are described herein. In an embodiment, a server stores a first plurality of digital electronic records identifying a plurality of past post-approved transactions by a first entity and a second plurality of digital electronic records for the first entity identifying a plurality of past pre-approved transactions by the first entity. The server uses a first machine learning system to determine that a subset of the first plurality of digital electronic records which identify a subset of the plurality of past post-approved transactions correspond to one or more pre-identified categories and a second machine learning system to match one or more particular digital electronic records of the subset of the first plurality of digital electronic records with one or more records of the second plurality of digital electronic records.

公开(公告)号：US11455637B2

公开(公告)日：2022-09-27

申请号：US16419438

申请日：2019-05-22

Applicant: Coupa Software Incorporated

Inventor： Kiran Ratnapu ,  Prasanna Kumar ,  Mikin Faldu ,  Fang Chang ,  Maggie M. Joy ,  Arjun Ramaratnam ,  Amit Vijayant

IPC: G06Q30/02 ,  G06Q20/40

Abstract: Computer-implemented techniques for repeatable and interpretable divisive analysis. In one embodiment, for example, a method comprises: identifying top-level cohorts of data items based on one or more characteristics of the data items in common; recursively or iteratively dividing a selected top-level cohort in a top-down manner resulting in a plurality of sub-level cohorts arranged in a hierarchy; detecting a particular data item that is a statistical outlier among data items of a leaf cohort in the hierarchy; and causing display of an indication in a computer user interface that the particular data item is an outlier.

公开(公告)号：US11449827B2

公开(公告)日：2022-09-20

申请号：US16676391

申请日：2019-11-06

Applicant: Coupa Software Incorporated

Inventor： Maggie Mae Joy ,  Daniel Benson ,  Fang-Kuey Chang ,  Kiran Ratnapu ,  Ankit Narang ,  Shoan Jain ,  Raghunandan Somaraju ,  Prasanna Kumar ,  Angela Welchel ,  Mikin Faldu ,  Dipeshkumar Vasantbhai Prajapati ,  Ketan Vasantkumar Darji ,  Rucha Apte

IPC: G06Q10/08 ,  G06N20/00

Abstract: Systems and methods for improving a computing system comparing past post-approved transaction records to past pre-approved transaction records are described herein. In an embodiment, a server stores a first plurality of digital electronic records identifying a plurality of past post-approved transactions by a first entity and a second plurality of digital electronic records for the first entity identifying a plurality of past pre-approved transactions by the first entity. The server uses a first machine learning system to determine that a subset of the first plurality of digital electronic records which identify a subset of the plurality of past post-approved transactions correspond to one or more pre-identified categories and a second machine learning system to match one or more particular digital electronic records of the subset of the first plurality of digital electronic records with one or more records of the second plurality of digital electronic records.