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    • 61. 发明申请
    • COMPUTER RECONCILIATION OF DATA FROM DISPARATE SOURCES
    • US20170323393A1
    • 2017-11-09
    • US15192593
    • 2016-06-24
    • Coupa Software Incorporated
    • Stephen CussenChristopher Yin
    • G06Q40/00G06F17/30
    • A method and system for reconciliation of data from disparate sources is provided. The method comprises storing a plurality of records, each record of the plurality of records associated with a source of the record, a category of the record of a plurality of categories, and one or more dates associated with the record; receiving a first record associated with a first range of dates and a first category of the plurality of categories; generating a first trip record from the first record, the first trip record associated with the dates in the first range of dates; receiving, from a first source, a second record associated with a first date, and a second category of the plurality of categories; associating the second record with the first trip record in response to determining that the first date is one of the dates in the first range of dates; receiving, from a second source, a third record associated with the first date, and the second category of the plurality of categories; associating the third record with the first trip record in response to determining that the first date is one of the dates in the first range of dates; combining the second record and the third record resulting in a merged record in response to determining that the second record and the third record are both associated with the first date, and the second category; determining an amount associated with the merged record by selecting the first source or the second source.
    • 63. 发明申请
    • FEEDBACK VALIDATION OF ELECTRONICALLY GENERATED FORMS
    • 电子生成形式的反馈验证
    • US20160196254A1
    • 2016-07-07
    • US15068239
    • 2016-03-11
    • Coupa Software Incorporated
    • Donna WilczekGabriel PerezRobert BernshteynRaja HammoudDavid Williams
    • G06F17/24
    • G06F17/243G06F17/248G06K9/00449
    • A method and apparatus for form processing is provided, requiring little to no data entry. Upon receiving an electronic notification containing a form, a validation server extracts an electronic contact address from the electronic notification. The validation server then applies a template associated with the sender's electronic contact address to a document to extract information necessary to generate an electronic form comprising machine parsable data. The sender is then granted access and prompted to validate the electronic form. The sender entity validates the electronic form by making any necessary changes or revisions and by submitting the editable web form. The form's parsable content is then stored directly as data in a database. In some embodiments, the validation server may accept the electronic validation with additional revision information. In these embodiments, the revision information may be applied to future forms received from the sender. Optionally, the revision information may also be used to create a new version of the template specifically associated with the sender's electronic contact address.
    • 提供了一种用于表单处理的方法和装置,需要很少或没有数据输入。 验证服务器在收到包含表单的电子通知后,从电子通知中提取电子联系地址。 然后,验证服务器将与发送者的电子联系人地址相关联的模板应用于文档以提取生成包括机器可解析数据的电子表单所需的信息。 然后发送者被授予访问权限并提示验证电子表单。 发件人实体通过进行任何必要的更改或修订以及提交可编辑的网络表单来验证电子表单。 然后将表单的可解析内容直接作为数据存储在数据库中。 在一些实施例中,验证服务器可以接受具有附加修订信息的电子验证。 在这些实施例中,修订信息可以应用于从发送者接收的未来表单。 可选地,修订信息还可以用于创建与发送者的电子联系人地址专门相关联的模板的新版本。
    • 65. 发明公开
    • DE-DUPLICATING TRANSACTION RECORDS USING TARGETED FUZZY MATCHING
    • US20240264989A1
    • 2024-08-08
    • US18427309
    • 2024-01-30
    • Coupa Software Incorporated
    • Jyotirmaya MahantaAnkit NarangShoan JainPrasanna Kumar
    • G06F16/215G06V30/19G06V30/412
    • G06F16/215G06V30/19093G06V30/412
    • 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.